Research Paper
Forecasting, production planning, and control
Akbar Abbaspour Ghadim Bonab
Abstract
Demand forecasting can have a significant impact on reducing and controlling companies' costs, as well as increasing their productivity and competitiveness. But to achieve this, accuracy in demand forecasting is very important. On this point, in the present study, an attempt has been made to analyze ...
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Demand forecasting can have a significant impact on reducing and controlling companies' costs, as well as increasing their productivity and competitiveness. But to achieve this, accuracy in demand forecasting is very important. On this point, in the present study, an attempt has been made to analyze the time series related to the demand for a type of women's luxury handbag based on a framework and using machine learning methods. For this purpose, five machine learning models including Adaptive Neuro-Fuzzy Inference System (ANFIS), Multilayer Perceptron Neural Network (MLPNN), Radial Basis Function Neural Network (RBFNN), Discrete Wavelet Transform - Neural Networks (DWTNN), and Group Model of Data Handling (GMDH) were used. The comparison of the models was also based on the accuracy of the forecasting according to the values of forecasting errors. The RMSE, MAE error measures as well as the R, correlation coefficient were used to assess the forecasting accuracy of the models. The RBFNN model had the best performance among the studied models with the minimum error values and the highest correlation value between the observed values and the outputs of the model. But in general, by comparing the error values with the data range, it is concluded that the models performed reasonably well.
Research Paper
Computational modelling
Reza Habibi
Abstract
The change point problem arises in various practical fields such as Epidemiology, Toxicology, Medical, Economical surveys, Quality control, Statistical process control, Natural events, Demography and Mortality. The aim of this study is to detect location and time of change point in Poisson regression ...
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The change point problem arises in various practical fields such as Epidemiology, Toxicology, Medical, Economical surveys, Quality control, Statistical process control, Natural events, Demography and Mortality. The aim of this study is to detect location and time of change point in Poisson regression model. We assume for years before and after , has a Poisson distribution with means and , respectively. We used several methods for estimation change point in real mortality data by assume Poisson regression model. Using two simulated and real data analysis showed that the change point has been occurred in year 1993 and this confirmed by all methods. Our findings have shown that the change pattern of mortality trend in Iran is related to improvement of health indicators and decreasing mortality rate in Iran.
Research Paper
Data Envelopment Analysis, DEA
Mahnaz Maghbouli; Fatemeh Moradi
Abstract
Emotional intelligence (EQ) is considered as an alternative issue in both fields of psychology and education. Studies that have been conducted in this area illustrate the role of emotional intelligence (EQ) and its components in different aspects of one's life such as academic achievement, occupation, ...
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Emotional intelligence (EQ) is considered as an alternative issue in both fields of psychology and education. Studies that have been conducted in this area illustrate the role of emotional intelligence (EQ) and its components in different aspects of one's life such as academic achievement, occupation, and social relationships. Turning to a view to academic performance measurement, mathematics is considered as a science which can promote the learners' ability in order to respond to the ups and downs of every individual’s life. Most of the previous papers have investigated the relationship between EQ and mathematical Performance. The main feature of those studies were focusing on statistical analysis. To deal with this issue, this study proposes an alternative procedure not only is interested in employing non parametric models, such as Data Envelopment Analysis (DEA), but also provides the statistical analysis to assess the questioned relation. The proposed procedure can serve as an evaluation tool for educational policy and students ‘promotion. To do so, eighty-one individuals have been selected among Islamic Azad University (Yadegar -e- Imam Khomeini (RAH) branch) engineering students with simple random during the first midterm of academic year 2019-2020. Distributing a standard EQ questionnaire of Bradberry (2005) reveals EQ and its four components’ scores. The average of three completed math scores have presented mathematical performance quantity. The results of Data Envelopment Analysis (DEA) point out no specific pattern between EQ and mathematical performance. The study also reveals that statistical analysis show a similar trend as efficiency analysis method did.
SI: AMCDMMI
Decision analysis and methods
Adel Azami; Hanif Kazerooni; Hossein Mohammadkhani Ghiasvand
Abstract
The production and service functions in the innovation system emphasize producing new products. As any innovation system’s final output must ultimately produce new products and deliver new services, the considered function is essential in the innovation system. This study seeks to extract the challenges ...
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The production and service functions in the innovation system emphasize producing new products. As any innovation system’s final output must ultimately produce new products and deliver new services, the considered function is essential in the innovation system. This study seeks to extract the challenges and give solutions to improve the production and deliver services in the innovation system. Producing and delivering services does not occur in a vacuum and should occur in a context called the supply chain (SC). In this paper, qualified experts were interviewed to discover the challenges and solutions to improve production. Fifteen elite researchers in the innovation field then discussed the results in focus sessions and refined practical solutions after an in-depth review of the extracted information. The role of responsible institutions was determined, and the necessary indicators were extracted to evaluate the factors of innovative production after providing the required infrastructure to achieve production promotion. One of the Fuzzy Multi-Attribute Decision Making (FMADM) techniques is also used to prioritize the discovered solutions based on the importance of influencing the producing promotion. Finally, a model is presented for improving the production and service functions in the innovation system. The results showed the main solution is to collaborate and create efficient integration at different SC levels.
SI: AMCDMMI
Operations Research
Vahid Razmjoei; Iraj Mahdavi; Selma Gutmen
Abstract
A cellular manufacturing system (CMS) is a suitable system for the economic manufacture of part families. Scheduling the manufacturing cells plays an effective role in successful implementation of the manufacturing system. Due to the fact that in the CMS, bottleneck machine and human resources are two ...
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A cellular manufacturing system (CMS) is a suitable system for the economic manufacture of part families. Scheduling the manufacturing cells plays an effective role in successful implementation of the manufacturing system. Due to the fact that in the CMS, bottleneck machine and human resources are two important factors, which so far have not been studied simultaneously in a mathematical model, there should be a model to consider them. Therefore, this research develops a bi-objective model for CMS in a three-dimensional space of machine-part and human resources. The main objective is to minimize the maximum completion time of all tasks in the system and reduce the number of intercellular translocation based on bottleneck machines’ motion and human resources. Due to the NP-hardness of the studied problem, applying the conventional solution methods is very time-consuming, and is impossible in large dimensions. Therefore, the use of metaheuristic methods will be useful. The accuracy of the proposed model is investigated using LINGO by solving a small example. Then, to solve the problem in larger dimensions, a hybrid Multi-Objective Tabu Search-Genetic Algorithm (MO-TS-GA) is designed and numerical results are reported for several examples.
SI: AMCDMMI
Data Envelopment Analysis, DEA
Mehdi Soltanifar
Abstract
Linear Assignment (LAM) is one of the Multi-Attribute Decision Making (MADM) methods that uses integer programming models in the solution process. In this method, only the final priority of the alternatives is determined and the distance between the alternatives is not clear. The purpose of this paper ...
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Linear Assignment (LAM) is one of the Multi-Attribute Decision Making (MADM) methods that uses integer programming models in the solution process. In this method, only the final priority of the alternatives is determined and the distance between the alternatives is not clear. The purpose of this paper is to modify this method so that instead of the final priority of the alternatives, the final weight of the alternatives is presented. This is done using a linear programming model of Data Envelopment Analysis (DEA). In this paper, we propose a hybrid MADM-DEA method called Linear Assignment Voting (VLAM). The new method is explained with a numerical example. The method will then be implemented on a problem in the real world to demonstrate the application of the method. In this case study, VLAM demonstrates the prioritization of models proposed by experts for the purchase of excavators in a road construction company. Also, based on the results of this method, the weight of the first, second and third priorities are 0.39, 0.35 and 0.26, respectively. These results increase the decision maker's power in making the final decision and choice.
Research Paper
Engineering Optimization
Golam Sakaline; Md. Aqib Aman; Md. Mahraj Uddin; Kaushik Debnath; Md. Abu Shahed; Tanver Rahman
Abstract
Bangladesh is blessed with various agro-based natural resources like Date sap, extracted from date trees. As this date sap is found in rural areas in large quantities annually but a very small fraction is converted into some value-added delicious foods at a domestic level while a large portion is left ...
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Bangladesh is blessed with various agro-based natural resources like Date sap, extracted from date trees. As this date sap is found in rural areas in large quantities annually but a very small fraction is converted into some value-added delicious foods at a domestic level while a large portion is left underutilized due to negligence, improper collection, and preservation system from the industry level. The processed delicious foods have conspicuous demand in the national market due to their nutritious value and the growth of the national economy. Despite its economic importance, very little researches have been conducted in this field for its industrial processing. So, this research implies to improve this straggled sector providing much attention for collecting raw sap from source and processing into value-added products from industrial level cost-effectively. The key objectives of this paper are to determine optimal facility location for processing date sap and set vehicle routes that can pick up date sap from source to processing plant simultaneously curtailing operational transportation costs. Initially, a Mixed Integer Linear Programming (MILP) model is introduced to determine optimal facility location. Besides, the Large Neighborhood Search (LNS) algorithm has been used to find the optimal set of vehicle routes. This paper outlines a summary of final results that Jessore (A south-western city in Bangladesh) is an optimal plant location and 10 vehicles are necessary for covering 15 areas which ultimately optimize the total supply time, respecting constraints concerning routing, timing, capacity, and supply as well transportation costs.
Research Paper
Management and Entrepreneurship
Younos Vakil Alroaia
Abstract
The aim of this study is providing a developed model for SMEs' in open innovation activities. In this regard, an appropriate model was defined by studying the literature. Then, after selecting a sample of 60 small and medium enterprises the data were collected by a questionnaire and were analyzed with ...
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The aim of this study is providing a developed model for SMEs' in open innovation activities. In this regard, an appropriate model was defined by studying the literature. Then, after selecting a sample of 60 small and medium enterprises the data were collected by a questionnaire and were analyzed with the Smart PLS software. In the third stage, the relative importance of factors was tested from the perspective of 10 experts in the field of open innovation along with experienced managers of the small and medium enterprises with more than 15 years of work experience with the help of ANP and PROMETHEE methods. The results showed that these factors include the parameters: Product Characteristics, Inter-organizational Factors, and Environmental Factors. In addition, the most important factors include Product Characteristics. Finally, several implications were made such as changing the degree of SMEs' participation in open innovation activities over time according to continuous monitoring of these moderators.
SI: AMCDMMI
Decision analysis and methods
Parviz Banafshi; Soleyman Iranzadeh; Houshang Taghizadeh
Abstract
The business process turbulence and the increasing competition among business firms have made the environment around organizations much different than before. Knowing the future business paths and moving in their direction in a way that benefits the organization indicates the necessity of marketing research ...
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The business process turbulence and the increasing competition among business firms have made the environment around organizations much different than before. Knowing the future business paths and moving in their direction in a way that benefits the organization indicates the necessity of marketing research and concepts such as market-centric. This study aims to evaluate the impact of market-centric on organizational performance by emphasizing the mediating role of organizational innovation in the value chain and provide a model for it. This research is a descriptive-survey study. Confirmatory factor analysis (CFA) technique has been used to evaluate the significance of regression weight (factor loading) of different constructs of the questionnaire in predicting the relevant items. LISREL statistical analysis software has been used to test the research hypotheses and analysis of structural equations. The statistical population of the study is all managers and employees working in the value chain of poultry industry in Kurdistan province, which 205 samples have been selected based on Cochran's formula. The results of data analysis indicate that the relationship between customer-centric and inter-task coordination with organizational innovation as well as the relationship between pivotal competition and organizational innovation with the financial performance of the organization was confirmed. There is no significant relationship between pivotal competition and organizational innovation, as well as between customer-centric and inter-task coordination with financial performance of the organization. Finally, some suggestions have been made to improve the performance of the poultry industry.
Research Paper
Computational modelling
Eshetu Dadi Gurmu; Boka Kumsa Bole; Purnachandra Rao Koya
Abstract
In this paper, optimal control problem is applied to Human Papillomavirus (HPV) and Herpes simplex virus type 2 (HSV-2) coinfection model formulated by a system of ordinary differential equations. Optimal control strategy is employed to study the effect of combining different intervention strategy on ...
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In this paper, optimal control problem is applied to Human Papillomavirus (HPV) and Herpes simplex virus type 2 (HSV-2) coinfection model formulated by a system of ordinary differential equations. Optimal control strategy is employed to study the effect of combining different intervention strategy on the transmission dynamics of HPV-HSV-II coinfection diseases. The necessary conditions for the existence of the optimal controls are established using Pontryagin’s Maximum Principle. Optimal control systems were performed with help of Runge-Kutta forward-backward sweep numerical approximation method. Finally, numerical simulation illustrated that a combination of all controls is the most effective strategy to minimize the disease from the community. The results shows that the size of infectious population are minimized by using different control strategies.
Research Paper
Decision analysis and methods
Nima Hamta; Mohammad Ehsanifar; Arezoo Babai; Abbas Biglar
Abstract
The purpose of this paper is to develop a new Failure Mode and Effect Analysis (FMEA) framework for identification, prioritization and improvement of failure modes. A hybrid multiple criteria decision-making (MCDM) method combining Stepwise Weight Assessment Ratio Analysis (SWARA) and VlseKriterijumska ...
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The purpose of this paper is to develop a new Failure Mode and Effect Analysis (FMEA) framework for identification, prioritization and improvement of failure modes. A hybrid multiple criteria decision-making (MCDM) method combining Stepwise Weight Assessment Ratio Analysis (SWARA) and VlseKriterijumska optimizacija I KOm-promisno Resenje (VIKOR) is used to rank the risk of failure modes identified in FMEA. For this purpose, the SWARA method is utilized to obtain the influential weights and then VIKOR technique is employed to give the prioritization levels for the failure modes in safety equipment. A case study of a gas company in Lorestan Province (Iran) is provided to illustrate the potential application and benefits of the proposed FMEA approach. The obtained results show that the new risk priority model can be effective to find high risk failure modes and create suitable maintenance strategies. The proposed FMEA also can overcome the shortcomings, improve the effectiveness of the traditional FMEA and provide useful information to help in managing risks of safety equipment.
Research Paper
Management and Entrepreneurship
Younos Vakil Alroaia; Samira Nazari Ghazvini
Abstract
The present research aims to design a model for the creation and development of knowledge-based cooperative companies in Semnan province by a mixed qualitative-quantitative approach. The qualitative approach was based on grounded theory and the quantitative approach was based on structural equation analysis. ...
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The present research aims to design a model for the creation and development of knowledge-based cooperative companies in Semnan province by a mixed qualitative-quantitative approach. The qualitative approach was based on grounded theory and the quantitative approach was based on structural equation analysis. In terms of purpose, this research is an applied study, and in terms of method, it is a descriptive survey study. The population includes the knowledge-based companies of Semnan province. Out of the mentioned data collection was done by library studies and semi-structured interviews in the qualitative phase and questionnaire in the quantitative phase. In the qualitative phase, the factors and the data obtained from the interviews were analyzed by Atlas.ti8 and grounded theory coding proposed by Strass and Corbin. The components and indicators of the creation and development of knowledge-based cooperative companies were identified on this basis. In the quantitative phase, Lisrel software and IBM SPSS statistics.26 software were used to apply the interpretive structural equation for developing the final research model. The findings include the indicators of components of creation, and development of knowledge-based cooperative companies in Semnan province and the model proposed for this purpose. The most important of these components: Education and research, Technology, Management strategies and policy-making, New platforms and infrastructures, Expansion of knowledge application, Knowledge-based innovation and creativity.
Research Paper
Supply chain management
Elham Shadkam; Mahdiyar Cheraghchi
Abstract
One of the stages of crisis management is planning and initial preparation to deal with the crisis. During natural disasters, one of the main activities is the logistics of relief groups and the activities of relief teams to save the lives of the victims of the accident. A review of past events shows ...
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One of the stages of crisis management is planning and initial preparation to deal with the crisis. During natural disasters, one of the main activities is the logistics of relief groups and the activities of relief teams to save the lives of the victims of the accident. A review of past events shows that the chances of rescuing the injured decrease and that a quick and correct decision is important in this situation. This paper presents a two-phase hybrid approach to decision-making and prioritization of affected regions to send relief teams. In this approach, multi-criteria decision-making methods in two phases are used to consider different indicators in achieving the optimal solution. In the first phase, with the help of the primary decision matrix, the AHP, TOPSIS and AHP-TOPSIS methods are used. And in the second phase, according to the results obtained from the first phase, the secondary decision matrix is created. With the CoCoSo method's help, one of the newest methods in this field, areas are prioritized for relief. In order to implement the proposed approach, the city of Amol has been studied.
Review Paper
Other
Kapil Gupta
Abstract
5S is an important industrial engineering technique which is used worldwide in a wide range of industrial and service type organizations for workplace management. Improvement in efficiency and productivity, and reduction in waste and idle time etc. are some of its benefits. This paper presents a fundamental ...
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5S is an important industrial engineering technique which is used worldwide in a wide range of industrial and service type organizations for workplace management. Improvement in efficiency and productivity, and reduction in waste and idle time etc. are some of its benefits. This paper presents a fundamental understanding of 5S technique and review of some important past work on implementation of 5S in various organizational setups. It is worth mentioning that safety has been identified as to be included as the 6th S under this technique. The main aim of this paper is to facilitate scholars, researchers, and engineers of industrial engineering field by providing knowledge and develop understanding of 5S technique so that they may further implement it in various scenarios of the workplace organization
Research Paper
Quality Control
Nazila Adabavzeh; Mehrdad Nikbakht
Abstract
The airline industry plays a fundamental role in the economic and social development of societies and it also has an important impact on improving foreign trade. The airline industry is one of the main infrastructures for sustainable development of the country. The quality of the reverse engineering ...
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The airline industry plays a fundamental role in the economic and social development of societies and it also has an important impact on improving foreign trade. The airline industry is one of the main infrastructures for sustainable development of the country. The quality of the reverse engineering service of the airline industry will be effective in increasing the safety and health of structures, reducing the impact of disasters and reducing costs. The airline industry needs its own defined models to measure the quality of service which has the ability to assess the quality of the services of this industry. Purpose of this research is to present a developed SERVQUAL model to assess the quality of services in the air industry. The RL AIRQUAL Model was a descriptive and cross-sectional analysis of reverse-customer support services of six organizational units of the air industry company using a 35-item questionnaire with standard 5-point Likert scale and adjusted SERVQUAL in eight dimensions of tangibility, reliability, assurance, empathy, responsiveness, safety and security, customer satisfaction and customer loyalty dimensions.Data were analyzed by paired t-test using SPSS software.Based on the determination of reverse service supportquality, the responsivenesshad the highest gap and safety and security had the lowest gap.The results can be used to assess the competitive position of the organization and identifying opportunities for improving the airline industry.With the help of the results of the modified model evaluation, applicable and suitable solutions can be developed to improve customer satisfaction.
Research Paper
Performance evaluation and benchmarking
Hamid Ghasemi; Mahyar Javid Ruzi; Mohammad Taghi Nazarpur
Abstract
Contractors help the government in carrying out construction and service projects. To reduce the risks resulting from the preparation and implementation of construction projects, the insurance industries should cooperate to include risk management. Contractors are facing many challenges regarding their ...
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Contractors help the government in carrying out construction and service projects. To reduce the risks resulting from the preparation and implementation of construction projects, the insurance industries should cooperate to include risk management. Contractors are facing many challenges regarding their insurance. Therefore, in this study, significant attention has been paid to identifying and ranking the challenges of contractor insurance in construction projects. The required information has been collected through the Delphi method and the opinions of experts in contracting companies. To identify the challenges, an open-ended questionnaire was distributed among the experienced insurance officials and 38 challenges have been identified. The relevant challenges formed the basis of a closed-ended questionnaire and the respondents were asked to re-evaluate their accuracy. Then, the approved challenges were the basis of the fuzzy best-worst method for weighing and ranking the related challenges. The results showed that the failure to provide specific consultation to contractors regarding the legal obligations of social security is the most important challenge in the field of contract insurance.
Research Paper
Decision analysis and methods
Davood Yaghoobi; Seyed Mahmoud Hashemi; Abdollah Naami
Abstract
This research is conducted with the aim of providing an effective advertising pattern based on social networks in the educational businesses industry. This research is applied in terms of objective, and survey-exploratory in terms of approach. The statistical population of this study was a group of experts ...
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This research is conducted with the aim of providing an effective advertising pattern based on social networks in the educational businesses industry. This research is applied in terms of objective, and survey-exploratory in terms of approach. The statistical population of this study was a group of experts including senior managers of private sector educational institutions, university professors and marketing consultants familiar with the private educational services industry that in-depth interviews were conducted with them. The selection of experts and doing interview with them continued until the theoretical saturation was reached and then stopped. Snowball sampling method was used in this research, and this process continued until reaching the theoretical saturation. 9 interviews were conducted in total. Due to using the data foundation theory in this research, the main data collection tool was unstructured in-depth interviews with experts. Finally, after three open, axial and selective kinds of coding, the conceptual model of the research was designed based on a paradigm model. Also in this study, using AHP decision method, research variables were prioritized according to experts.
Research Paper
Data Envelopment Analysis, DEA
Mohammad Khodabakhshi; Zahra Cheraghali
Abstract
One of the critical concerns in the Audit Court is to study budgetary deviations of the executive organizations. Audit Court seeks methods to evaluations the executive organizations based on their budget deviations. The aim of this study is to rank executive agencies aimed at the improvement of their ...
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One of the critical concerns in the Audit Court is to study budgetary deviations of the executive organizations. Audit Court seeks methods to evaluations the executive organizations based on their budget deviations. The aim of this study is to rank executive agencies aimed at the improvement of their performance. We use a ranking method based on data envelopment analysis that can simultaneously use multi-indexes for ranking and we use budget split indexes of the Audit Court for ranking of executive organizations. The results enable managers to identify the best and worst executive agencies based on the considered indexes of the budget split of the Audit Court. The objectives of this paper are to investigate which executive organizations have more budget deviations. Any organization that had a lower rank shows that it has based on the indexes under evaluation more deviation. To study the performance process of each of the executive agencies, we collected data for two years and analyzed the performance of the executive agencies during these two years.
Research Paper
Engineering Modeling
salman Abbasi Siar; MohammadAli Keramati; Mohammad Reza Motadel
Abstract
Because of the dissemination of impulse buying behavior in consumers its academic studies have increased over the last decade. Because in large stores, sales have to be increased, the behavior of consumers in impulse buying to be taken into account by the researchers and managers of the stores. The purpose ...
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Because of the dissemination of impulse buying behavior in consumers its academic studies have increased over the last decade. Because in large stores, sales have to be increased, the behavior of consumers in impulse buying to be taken into account by the researchers and managers of the stores. The purpose of this paper is to model agent-based the impulse buying behavior of consumers (customers), with regards to the factors of discount and swarm in the purchase. In terms of executive purpose and with agent-based modeling approach, the present paper examines the existing reality of consumer impulse buying behavior. This paper develops consumption models, examines and analyzes consumer behavior under the NetLogo software environment. In comparing the optimal points of discounts and sales volume in both discount and swarm-discount functions that lead the stores to maximize profits and sales volume simultaneously, it can be debated that with running this model (swarm-discount) stores would be gaining more sales by less discounts. Results could describe customer behavior by implementing discount and swarm factors. Understanding the Customer behavior prepared the comparing possibility of customer behavior in store in each introduced mathematical model. The contributions could be considered in two points of view. On the applicable view, this research can provide the managers and decision makers with significant information, includes possibility of forecasting sales volume and incomes of any policies in stores, so the comparing of policies and strategies analysis would be possible. This method is rather less expensive, because of virtual environment nature. Users of this model can study other sections by changing the research assumptions.
SI:Big Data and Artificial Intelligence (BDAI)
Supply chain management
Reza Tavakkoli-Moghaddam; Javid Ghahremani-Nahr; Paria Samadi Parviznejad; Hamed Nozari; Esmaeil Najafi
Abstract
This paper examines the use of the Internet of Things (IoT) in the Food Supply Chain (FSC) and identifies the strengths and weaknesses of this system. Since this paper is a review study, the papers published from 2014 to June 2021 have been studied and 93 articles related to the field of IoT applications ...
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This paper examines the use of the Internet of Things (IoT) in the Food Supply Chain (FSC) and identifies the strengths and weaknesses of this system. Since this paper is a review study, the papers published from 2014 to June 2021 have been studied and 93 articles related to the field of IoT applications in the FSC have been reviewed. By reviewing the literature, six basic applications obtained for this type of network include transportation procurement, food production, resource/waste management, food safety improvement, food quality maintenance, and FSC transparency. Clustering is used to achieve these. Cluster analysis suggests that researchers should pay more attention to IoT applications for product quality and transparency throughout the supply chain, and consider IT-based systems seamlessly at each level of the supply chain. Cluster analysis suggests that researchers should pay more attention to IoT applications for product quality and transparency throughout the supply chain, and consider IT-based systems seamlessly at each level of the supply chain.
Research Paper
Engineering Optimization
Osarobo Osamede Ogbeide; Kolawole Akeredolu; Samuel Ayodeji Omotehinse
Abstract
The service life of engineering structure is mostly affected by the quality and strength of the welded joints. Tensile tests are performed for several reasons. The results are used in selecting materials for engineering applications. Tensile properties are frequently included in material specifications ...
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The service life of engineering structure is mostly affected by the quality and strength of the welded joints. Tensile tests are performed for several reasons. The results are used in selecting materials for engineering applications. Tensile properties are frequently included in material specifications to ensure quality. The tests are measured during development of new materials and processes, so that different materials and processes can be compared. The objective of this study is to predict and optimize the tensile strength of a butt joint weldment on mild steel plate using response surface methodology. The response surface methodology was applied to predict and optimize the maximum tensile strength of a butt joint weldment on an I-section mild steel plate using tungsten inert gas (TIG) welding process. The mild steel plate was cut into dimension 60mm x 40mm x 10mm with a power hacksaw, grinded and cleaned before the welding process. The experimental matrix was made of twenty (20) runs, generated by the design expert 11.1.0.1 software adopting the central composite design. The response (tensile strength) was measured and then modelled using the response surface methodology. The result obtained show that the current and voltage has a very strong influence on the tensile strength. Based on the findings, the maximum tensile strength of 450Mpa was attained at the welding voltage (V) of 24V, current of 170A and gas flow rate of 13lit/min respectively. This study will serve as a guide to welding operators on parameter settings selection.
SI:Big Data and Artificial Intelligence (BDAI)
Case studies in industry and services
Najaf Ghrachorloo; Faramarz Nouri; Mostafa Javanmardi; Houshang Taghizadeh
Abstract
In the past years, East Azerbaijan Province in Iran has always been at the top of the number of incidents in the country in the reports related to the annual analysis of incidents of domestic natural gas subscribers. Despite planning and spending at the expense of previous years, there has been no significant ...
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In the past years, East Azerbaijan Province in Iran has always been at the top of the number of incidents in the country in the reports related to the annual analysis of incidents of domestic natural gas subscribers. Despite planning and spending at the expense of previous years, there has been no significant reduction in incident statistics. The purpose of this article is to investigate the root factors affecting the occurrence of incidents in domestic consumers of natural gas in East Azerbaijan province and to provide control and reduction strategies for incidents. To study the statistical analysis of natural gas-related incidents, the big data mining data approach of natural gas incidents in East Azerbaijan province during the years 2014 to 2020 besides Pareto analysis, root analysis, and Delphi have been used. The results of data and information analysis indicate that the most important technical factors affecting the bite are: lack of proper installation of the chimney, use of non-standard chimneys, leakage due to seams between the chimney parts, / the presence of cracks, and virtual blockage of the chimney.
Research Paper
Data Envelopment Analysis, DEA
Maryam Nematizadeh; Maryeh Nematizadeh
Abstract
Naturally, managers are interested in analyzing the relative efficiency of the production systems with parametric or non-parametric methods. One of the non-parametric methods utilized in recent three decades is a data envelopment analysis (DEA) that can evaluate the relative efficiency of these structures ...
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Naturally, managers are interested in analyzing the relative efficiency of the production systems with parametric or non-parametric methods. One of the non-parametric methods utilized in recent three decades is a data envelopment analysis (DEA) that can evaluate the relative efficiency of these structures and determine their strengths and weaknesses. In the real world, most production systems have a network structure. So, network data envelopment analysis (NDEA) is a suitable non-parametric method to evaluate the performance of production processes, which considers the internal processes. In addition to the importance of treating consumed waters and pollutants in environmental protection in today’s world, increasing the profitability of the production unit can be an important motivation to design the proper model to evaluate the performance of these structures in terms of profitability. In this sense, we first introduce a two-stage feedback structure including undesirable factors. Then, by applying the assumption of weak disposability for undesirable factors, a method for analyzing the relative performance of such network structures is given. The focus would be on profitability maximization. Moreover, to illustrate the proposed approach, a real case on the ecological system of 31 regions of China is used.
SI: ADLRTCA
Decision analysis and methods
Effat Jalaeian Zaferani; Mohammad Teshnehlab; Mansour Vali
Abstract
The personality in the present world plays a critical role in social interactions, the use of modern technologies, and individuals' success. Therefore, in the last two decades, the study of automatic personality perception and automatic personality recognition has become more prevalent than speech ...
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The personality in the present world plays a critical role in social interactions, the use of modern technologies, and individuals' success. Therefore, in the last two decades, the study of automatic personality perception and automatic personality recognition has become more prevalent than speech processing. These studies have shown that personality traits affect acoustic features. However, the intrinsic imbalanced distribution of personality classes across the dataset is an issue mentioned in most previous studies and the classification results suffer from it. In this paper, an innovative supervised k-fold cross-validation method was proposed to cope with the problem of affecting the imbalanced distribution of data across different classes. The classification outcomes showed better performance in comparison with three traditional data balancing methods. Moreover, the obtained results of the proposed evaluation method indicated that the proposed method acts as a k-fold cross-validation method if the data distribution is balanced; otherwise, it will improve the classification results.
Research Paper
Case studies in industry and services
Rasoul Jamshidi; Sattar Rajabpour Sanati; Morteza Zarrabi
Abstract
The saving banks of “umbilical cord blood stem cells” are considered as strategic health-based institutions in most countries. Due to the limited capacity of cord blood sample storage tanks, the samples should be evaluated according to their quality. So these banks need a method to assess ...
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The saving banks of “umbilical cord blood stem cells” are considered as strategic health-based institutions in most countries. Due to the limited capacity of cord blood sample storage tanks, the samples should be evaluated according to their quality. So these banks need a method to assess quality. In this paper, first, the effective factors on the quality index of the extracted cord blood from newborn infants are identified using the electronic records and database of Royan’s umbilical cord blood bank. Then by machine learning and various statistical methods such as multilayer perceptron neural networks, radial basis function neural networks, logistic regression, and C4.5 decision tree, the quality value of blood samples and their proper category (for discarding or freezing) are determined. Two different sets of data have been used to evaluate the proposed methods. The results show that the ensemble of radial basis function neural network with k-means clustering model has the best accuracy compared to other methods, which categorizes the samples with 91.5% accuracy for the first data set and 81.6% accuracy for the second one. The results also show that using this method can save about $1 million annually.
SI:Big Data and Artificial Intelligence (BDAI)
Heuristics and Metaheuristics Algorithms
Ali Sanagooy Aghdam; Mohammad Ali Afshar Kazemi; Abbas Toloie Eshlaghy
Abstract
Optimized asset tracking with radio frequency identification (RFID) as a complicated innovation that requires much money to be implemented has become more popular in the healthcare industry. Considering the use of more antennas in each reader, we present a modern heuristic methods, hybrid of genetic ...
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Optimized asset tracking with radio frequency identification (RFID) as a complicated innovation that requires much money to be implemented has become more popular in the healthcare industry. Considering the use of more antennas in each reader, we present a modern heuristic methods, hybrid of genetic algorithms (GA) and simulated annealing (SA) for the purpose of placing readers in an emergency department of a hospital with an RFID network. In this study, a multi-objective function is developed for the network coverage maximization and the minimization of total cost, tag reader collision, interference, energy consumption, and path loss in a simultaneous way. The proposed algorithm provides savings (on average) in the total cost of the RFID network through the efficient use of three types of readers with one, two and four antenna ports. Additionally, by testing three scenarios, the effect of algorithms in achieving the optimal solution is indicated by the simulated results. Besides, the results of GA-SA is compared to the results of GA and other existing models in the relevant literature. It is shown that its main advantage is the use of multi-antenna RFID readers, which reduces the total cost of the RFID network and also increase network coverage with fewer readers and antennas. In other words, contributions for the research are proposing a hybrid GA-SA algorithm, developing a multi-objective function, testing the algorithm in a hospital setting, and comparing the results of GA-SA with GA.
Research Paper
Case studies in industry and services
Farkhondeh Mortaz Hejri; Changiz Valmohammadi; Mahmood Alborzi
Abstract
This study aimed to identify factors affecting the green management process readiness of banks and determining the interactions and priority of these factors. To this end, factors affecting the green management process readiness in the banking industry were extracted by using an in-depth study of the ...
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This study aimed to identify factors affecting the green management process readiness of banks and determining the interactions and priority of these factors. To this end, factors affecting the green management process readiness in the banking industry were extracted by using an in-depth study of the extant research and qualitative content analysis. Also, fuzzy DEMATEL method was used to explain and assess the interrelationships between the identified factors. The research sample included 30 experts in the process management field in the industry and academicians with knowledge of the concepts of emerging technologies and more than 10 years of experience at the level of managerial activities in the banking industry. Application of DEMATEL revealed that “green awareness”, “green attitude”, “green governance”, and “green technology” are the influential factors, while “green operation”, “green infrastructure”, “green lifecycle”, “green strategy”, and “green policies” are permeable factors. It was also found that “green awareness” has the greatest impact on other factors and "green operations "is the most permeable factor. The obtained results might help to raise the awareness of individuals including managers, policymakers of the organizations toward establishing and fostering a green attitude to adopting green operations.
Research Paper
Supply chain management
Arash Khosravi; Seyed Reza Hejazi Taghanaki; Shahab Sadri; Anil Kumar; Hossein Arshad
Abstract
The objective of this study is to model a dynamic redesigning closed-loop supply chain network with capacity planning in order to minimize the costs of the network. The structure of this model consists of existing facilities including manufacturing plants, distribution and reworking centers. Any such ...
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The objective of this study is to model a dynamic redesigning closed-loop supply chain network with capacity planning in order to minimize the costs of the network. The structure of this model consists of existing facilities including manufacturing plants, distribution and reworking centers. Any such structure should change due to fluctuations in demand in order to meet customer demand. Establishing new facilities, closing the existing ones, and adding discrete capacity levels to facilities, are among the decisions which lead to necessary changes in network structure. To make the issue more realistic, it is assumed that demand and returned products are stochastic. To solve the problem, a two-stage stochastic mixed integer linear programming is modelled, followed by writing a robust counterpart of the MILP model program. An accelerated Benders decomposition algorithm is proposed to solve this model. To increase the convergence trend of this proposed algorithm, valid-inequalities and Pareto optimal cut are combined to the model. The expected performance improvement based on applying valid-inequalities and Pareto optimal cut is expressed through numerical results obtained from different samples.
Research Paper
Management and Entrepreneurship
Abbas Heravi; Afsaneh Zamani Moghadam; Seyed Ahmad Hashemi; Younos Vakil Alroaia; Abddulah Sajadi Jagharg
Abstract
Given the increased competition and turbulence in business environments, the proper management of human resources and employee growth is a significant challenge faced by organizations to achieve competitive advantage. The present study aimed to analyze the influential factors in human resource development ...
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Given the increased competition and turbulence in business environments, the proper management of human resources and employee growth is a significant challenge faced by organizations to achieve competitive advantage. The present study aimed to analyze the influential factors in human resource development (HRD) in state-owned enterprises (SOEs). This was an applied research in terms of objective and a mixed (qualitative-quantitative), exploratory study in terms of design. In the qualitative-quantitative section of the study, content analysis and descriptive-exploratory techniques were applied. Data were collected via semi-structured interviews and by using questionnaires in the qualitative and quantitative sections, respectively. The research population included human resource experts, managers, and experts in the field of human resource planning and SOE management. In total, 22 individuals were selected via purposeful sampling. In the qualitative section, data analysis was carried out using open, axial, and selective coding for the classification of the identified factors into four categories of organizational, occupational, behavioral, and empowerment factors. In addition, screening was performed using the Fuzzy Delphi method, and the correlations between the identified factors and sub-factors were determined using the Fuzzy DEMATEL method. According to the results, empowerment factors were the most significant determinants of HRD, which could be improved by considering the associated influential factors and prioritization of organizational factors. On the other hand, the factor weighting findings based on the fuzzy analytic network process indicated that among the identified factors and sub-factors of knowledge management, empowerment factors had the most significant impact on HRD.
Research Paper
Management and Entrepreneurship
Mohammad Javad Taghipourian; Elham Fazeli Veisari; Syed Mahmod Norashrafodin; Mohammad Verij kazemi
Abstract
Due to the increasing importance of marketing, entrepreneurship and the role of organizational structure in their application, the purpose of this research is to predict entrepreneurial marketing using an organizational structure in the insurance industry. For this purpose, for marketing, seven indicators ...
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Due to the increasing importance of marketing, entrepreneurship and the role of organizational structure in their application, the purpose of this research is to predict entrepreneurial marketing using an organizational structure in the insurance industry. For this purpose, for marketing, seven indicators and for organizational structure, three indicators are defined, then prediction of entrepreneurial marketing indicators has been done by organizational structure indicators using lazy learning algorithm. In the proposed method, after predicting each data by K vector from its closest neighbor, the algorithm database is enriched for better prediction of future data. The proposed algorithm is simulated and compared in five different modes by MATLAB software, also, three insurance (Iran, Karafarin and Parsiyan) companies are selected in Mazandaran province. In total, the statistical population in this study is 588 cases. The results of simulation indicate the proper accuracy of entrepreneurial marketing forecasting based on validation parameters MSE and NRMSD. In this research, Lazy Learning method can predict future without modeling the problem with previous information processing.
Research Paper
Data Envelopment Analysis, DEA
Rita de Fátima Muniz; Wagner Bandeira Andriola; Sheila Maria Muniz; Antônio Clécio Fontelles Thomaz
Abstract
The present article deals with the application of the Data Envelopment Analysis (DEA) methodology to identify the most weighty factors that are associated with student performance on large-scale assessments, amongst them, the Permanent Assessment System for Basic Education (SPAECE) test. The DEA Slacks-Based-Measure ...
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The present article deals with the application of the Data Envelopment Analysis (DEA) methodology to identify the most weighty factors that are associated with student performance on large-scale assessments, amongst them, the Permanent Assessment System for Basic Education (SPAECE) test. The DEA Slacks-Based-Measure (SBM) model was used to estimate the relative efficiency of school units in the city of Sobral (CE), one of the most prominent Brazilian counties in the educational scenario. It was evident that the presence of libraries, computer labs, sports courts and rooms for special care in school units constitutes a significant factor associated with the high performance of students, impacting, therefore, on school efficiency.
Research Paper
Decision analysis and methods
Vahid Mottaghi; Mahdi Esmaeili; Ghasem Ali Bazaee; Mohammadali Afshar Kazemi
Abstract
With the increase of news on social networks, a way to identify fake news has become an essential matter. Classification is a fundamental task in natural language processing (NLP). Convolutional neural network (CNN), as a popular deep learning model, has shown remarkable success in the task of fake news ...
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With the increase of news on social networks, a way to identify fake news has become an essential matter. Classification is a fundamental task in natural language processing (NLP). Convolutional neural network (CNN), as a popular deep learning model, has shown remarkable success in the task of fake news classification. In this paper, new baseline models were studied for fake news classification using CNN. In these models, documents are fed to the network as a 3-dimensional tensor representation to provide sentence-level analysis. Applying such a method enables the models to take advantage of the positional information of the sentences in the texts. Besides, analyzing adjacent sentences allows extracting additional features. The proposed models were compared with the state-of-the-art models using a collection of real and fake news extracted from Twitter about covid-19, and the fusion layer was used as the decision layer in selecting the best feature. The results showed that the proposed models had better performance, particularly in these documents, and the results were obtained with 97.33% accuracy for classification on Covid-19 after reviewing the evaluation criteria of the proposed decision system model.
Research Paper
Statistical Process
Nastaran Hajarian; farzad Movahedi Sobhani; Seyed Jafar Sadjadi
Abstract
One of the most complex and costly systems in the industry is the Gas turbine (GT). Because of the complexity of these assets, various indicators have been used to monitor the health condition of different parts of the gas turbine. Turbine exit temperature (TET) spread is one of the significant indicators ...
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One of the most complex and costly systems in the industry is the Gas turbine (GT). Because of the complexity of these assets, various indicators have been used to monitor the health condition of different parts of the gas turbine. Turbine exit temperature (TET) spread is one of the significant indicators that help monitor and detect faults such as overall engine deterioration and burner fault. The goal of this article is to use data-driven approaches to monitor TET data to detect faults early, as fault detection can have a significant impact on gas turbine reliability and availability. In this study, the TET data of v94.2 GT is measured by six temperature transmitters to show a detailed profile. According to the statistical tests, TET data are high dimensional and time-dependent in the real world industry. Hence, three distinctive methods in the field of the gas turbine are proposed in this study for early fault detection. Conventional principal component analysis (PCA), moving window PCA (MWPCA), and incremental PCA (IPCA) were implemented on TET data. According to the results, the conventional PCA model is a non-adaptive method, and the false alarm rate is high due to the incompatibility of this approach and the process. The MWPCA based on V-step-ahead and IPCA approaches overcame the non-stationary problem and reduced the false alarm rate. In fact, these approaches can distinguish between the normal time-varying and slow ramp fault processes. The results showed that IPCA could detect fault situations faster than MWPCA based on V-step-ahead in this study.
SI: RAIDSCM
Transportation
Sarow Saeedi; Omid Poursabzi; Zaniar Ardalan; Sajad Karimi
Abstract
Hub location problems (HLP) have multiple applications in logistic systems, the airways industry, supply chain network design, and telecommunication. In the HLP, the selected nodes as hubs perform the principal role in processing the inflow arising from other nodes. So, congestion would be inevitable ...
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Hub location problems (HLP) have multiple applications in logistic systems, the airways industry, supply chain network design, and telecommunication. In the HLP, the selected nodes as hubs perform the principal role in processing the inflow arising from other nodes. So, congestion would be inevitable at hub nodes. This paper considers a p-hub median problem with multiple hub node servers delivering service at variable rates. Since the service rates are limited and variable, a queue is formed at each hub server. To tackle this problem, we developed a mixed-integer linear programming model that optimizes the selected hub nodes to reduce congestion under an allowable defined queue length at each server and minimize the total costs of the model, including transportation and hub establishment costs. We utilized the Civil Aeronautics Board (CAB) dataset containing 25 USA cities, which is a valuable source for designing numerical examples in the HLP, to prove the model's efficiency. The results obtained from the designed sample problems show that strategic decisions on defining the number of hubs and maximum acceptable queue length at each hub server will significantly impact the hub location network design.
SI: ADLRTCA
Data mining
aboosaleh mohammad sharifi; kaveh khalili damghani; farshid abdi; soheila sardar
Abstract
Cryptocurrencies are considered as new financial and economic tools having special and innovative features, among which Bitcoin is the most popular. The contribution of the Bitcoin market continues to grow due to the special nature of Bitcoin. The investors' attention to Bitcoin has increased significantly ...
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Cryptocurrencies are considered as new financial and economic tools having special and innovative features, among which Bitcoin is the most popular. The contribution of the Bitcoin market continues to grow due to the special nature of Bitcoin. The investors' attention to Bitcoin has increased significantly in recent years due to significant growth in its prices. It is important to create a prediction system which works well for investment management and business strategies due to the high chaos and volatility of Bitcoin prices. In this study, in order to improve predictive accuracy, Bitcoin price dataset is first divided into a time interval through time window, then propose a new model based on long short-term memory neural networks (LSTM) and Metaheuristic Algorithms. Chaotic Dolphin Swarm Optimization Algorithm is used to optimize the LSTM. Performance evaluation indicated that the proposed model can have more effective predictions and improve prediction accuracy. In addition, the performance of the optimized model is better and more reliable than other models.
Research Paper
Decision analysis and methods
Shahla Jahangiri; Milad Abolghasemian; Adel Pourghader chobar; Ahmadreza Nadaffard; Vahid Mottaghi
Abstract
China introduces a new strain of coronavirus as a causative of a new respiratory disease after several people contracted an unusual pneumonia in December 2019. The World Health Organization stated that the outbreak of the virus resulted in public health emergencies around the world. Humanitarian supply ...
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China introduces a new strain of coronavirus as a causative of a new respiratory disease after several people contracted an unusual pneumonia in December 2019. The World Health Organization stated that the outbreak of the virus resulted in public health emergencies around the world. Humanitarian supply chain management is concerned with managing the efficient flow of aid materials, information and services and aim to reduce the impact of disaster on human lives. In this paper, provides a ranking for key resources in the humanitarian supply chain in the emergency department of Iranian hospital using hybrid decision-making method under COVID-19 conditions. According to the obtain results, Nurses in RK 1, Receptionists RK 2, General surgeon RK 3, Heart residents RK 4 and Pulmonologist RK 5. Hybrid decision-making method in this paper is an invaluable contribution to the emergency department and medical managers for evaluates of current situation Emergency Department when crisis occur.
SI: ADLRTCA
Information Retrieval
Ali Fallahi RahmatAbadi; Javad Mohammadzadeh
Abstract
With the exponentially increasing volume of online data, searching and finding required information have become an extensive and time-consuming task. Recommender Systems as a subclass of information retrieval and decision support systems by providing personalized suggestions helping users access what ...
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With the exponentially increasing volume of online data, searching and finding required information have become an extensive and time-consuming task. Recommender Systems as a subclass of information retrieval and decision support systems by providing personalized suggestions helping users access what they need more efficiently. Among the different techniques for building a recommender system, Collaborative Filtering (CF) is the most popular and widespread approach. However, cold start and data sparsity are the fundamental challenges ahead of implementing an effective CF-based recommender. Recent successful developments in enhancing and implementing deep learning architectures motivated many studies to propose deep learning-based solutions for solving the recommenders' weak points. In this research, unlike the past similar works about using deep learning architectures in recommender systems that covered different techniques generally, we specifically provide a comprehensive review of deep learning-based collaborative filtering recommender systems. This in-depth filtering gives a clear overview of the level of popularity, gaps, and ignored areas on leveraging deep learning techniques to build CF-based systems as the most influential recommenders.
Research Paper
Transportation
Vasilis Apostolopoulos; George Kasselouris
Abstract
One of the main topics with increasing interest in freight transport and logistics is developing efficient and sustainable supply chain strategies that best cover customer demands and expectations as well as identify considerable cost savings and emission reductions. This study focuses on the evaluation ...
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One of the main topics with increasing interest in freight transport and logistics is developing efficient and sustainable supply chain strategies that best cover customer demands and expectations as well as identify considerable cost savings and emission reductions. This study focuses on the evaluation of the potential of a logistics centre for consolidating and delivering goods at urban level, based on economic, social and environmental aspects, by performing both GIS simulation and SWOT analysis, while considering key criteria of transport management, infrastructure and fleet attributes as well as logistics and market features in the Attica region of Greece. The case refers to the largest Logistics Centre of Greece, located at Thriasio, offering door-to door services to the main industrial areas of the region. The approach followed, consists of two core elements: (1) a specific model of a last-mile delivery network in GIS environment, towards simulating and solving the vehicle routing problem (VRP) as well as b) a strategic assessment of the foreseen logistics activities through the SWOT business tool. For a transport operator with 5 vehicles, an operational distance-related cost of €1.8-1.9 per pallet was estimated. Results also show the lower environmental impact of larger vehicles due to transport pooling.
Research Paper
Human factors, ergonomics, and safety
Yousef Ravanpeykar; Afsaneh Zamani Moghadam; Seyyed Abdollah Sajadi Jaghargh; Seyyed Ahmad Hashemi; Zeynol Abedin Amini Sabegh
Abstract
Pathology of a competency-based human resource management system results in the managers developing appropriate schedules for employee growth and excellence to gain a competitive advantage. The present study is meant to be an applied study of a descriptive exploratory nature. Information and data gathering ...
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Pathology of a competency-based human resource management system results in the managers developing appropriate schedules for employee growth and excellence to gain a competitive advantage. The present study is meant to be an applied study of a descriptive exploratory nature. Information and data gathering involves library and field research making use of interviews and questionnaires. The statistical population of this study is comprised of experts including 10 human resource managers and chief officers, selected using a targeted method. The components were determined and analyzed using the experts’ opinions and the Delphi method; furthermore, by implementing the importance-performance analysis, low-performance but high-importance components were categorized in 6 groups of “Human Resource Supply System”, “Human Resource Training and Development System”, “Human Resource Retention System”, “Human Resource Labor Relations System”, “Human Resource Performance Management System”, “Human Resource Reward System”. Moreover, to rectify the problems, the Fuzzy DEMATEL method was implemented with the results showing the “Human Resource Supply System” problem to be the most effective, eventually leading to the problem of “Human Resource Performance Management System”, being the most affected. Managers can reach a desirable human resource management system by identifying individuals of professional competence to compete in a dynamic economy.
SI:Big Data and Artificial Intelligence (BDAI)
Data mining
Ramez Kian; Hadeel S Obaid
Abstract
Human life today is intertwined with abundant trade and economic exchanges, and life would not be possible without trade and commerce. One of the main pillars of financial exchanges are banks and financial and credit institutions, which, as the vital arteries of the economy, are responsible for transferring ...
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Human life today is intertwined with abundant trade and economic exchanges, and life would not be possible without trade and commerce. One of the main pillars of financial exchanges are banks and financial and credit institutions, which, as the vital arteries of the economy, are responsible for transferring funds and keeping the economy alive. In the world of economic competition between organizations, profitability and proper performance for stakeholders are the basic principles of the organization's survival. To increase profitability, banks must take measures that, in addition to reducing costs, increase the level of service and customer satisfaction. The best way to do this is to use new technologies and orient the bank's policies to provide services in person and independent of time and place. The use of new technologies in the banking system sometimes leads to customers' distrust and distrust of the bank. Therefore, solutions to detect fraud in banking transactions should be provided. This article aims to discover a model for face-to-face transactions and to establish a system to block fraudulently issued transactions. Therefore, a big data clustering method is designed to timely identify bribery in banking transactions. The results show that using the big data clustering method in the fastest time can detect and stop possible fraud in customers' banking transactions.
SI:RSSCMMA
Supply chain management
Mohammad Reza Razdan; Saeed Aghasi; Sayyed Mohammad Reza Davoodi
Abstract
Supply chain risk management involves identifying, ranking, and adopting appropriate strategies to control and deal with risks that could disrupt chain performance. These risks can be caused by different issues and descriptions and surveys about these risks are associated with uncertainty, ambiguity, ...
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Supply chain risk management involves identifying, ranking, and adopting appropriate strategies to control and deal with risks that could disrupt chain performance. These risks can be caused by different issues and descriptions and surveys about these risks are associated with uncertainty, ambiguity, qualitativeness and incomplete and sometimes contradictory information. Therefore, their ranking needs the techniques that can model the mentioned issues. neutrosophic logic makes it possible to model propositions with uncertainty, incomplete information, ambiguity, qualitativeness, and even inconsistency. Accordingly, the approach of the present study is to use a combined method of neutrosophic hierarchical analysis and TOPSIS for ranking the risk. Core of this paper is proposed a hybrid decision making method for identification and ranking of supply chain management by a Neutrosophic analytical hierarchy process and TOPSIS approach. The case study is Mobarakeh Steel Company of Isfahan and three criteria including resilience, agility and robustness are considered as major strategies to deal with risk and seventeen risk-related issues are ranked as options. The results show that government constraints, economic and environmental risks, inventory shortages, technology risk, forecast risk and financial (cash) problems are the most important risks threatening the supply chain. Therefore, we believe that the proposed framework provides managers with valuable knowledge for decision making.
SI:Big Data and Artificial Intelligence (BDAI)
Data mining
amir daneshvar; Fariba Salahi; Maryam Ebrahimi; Bijan Nahavandi
Abstract
The aim of analyzing passengers' behavioral patterns is providing support for transportation management. In other words, to improve services like scheduling, evacuation policies, and marketing, it is essential to understand spatial and temporal patterns of passengers' trips. Smart Card Automated ...
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The aim of analyzing passengers' behavioral patterns is providing support for transportation management. In other words, to improve services like scheduling, evacuation policies, and marketing, it is essential to understand spatial and temporal patterns of passengers' trips. Smart Card Automated Fare Collection System (SCAFCS) makes it possible to utilize data mining tools for the purpose of passengers' behavioral pattern analysis. The specific goal of this research is to obtain functional information for passenger's behavioral pattern analysis in city express bus which is called BRT, and classification of passengers to improve performance of bus fast transportation system. Additionally, it is attempted to predict usage and traffic status in a line through predicting passenger's behavior in a bus line. In this paper, smart card data is applied to provide combinational algorithms for clustering and analysis based on data mining. To this end, we have used a combination of data mining methods and particle swarm optimisation algorithm and leveraged multivariate time series prediction to estimate behavioral patterns. Results show that price and compression ratio features are the most influencing features in the separability of transportation smart card data. According to obtained Pareto front, four features include a card identification number, bus identification number, bus line number, and charge times are influencing clustering criteria.
SI:RSSCMMA
Inventory, logistics, and transportation
Adel Pourghader chobar; Majid Sabk Ara; Samaneh Moradi Pirbalouti; Mehdi Khadem; Saeed Bahrami
Abstract
During natural and abnormal accidents, many people are injured, and a large number of wastes and rubbish are produced, so it is necessary to collect the injured and take them to treatment centers, which must be done in the reaction phase. Also, in the recovery and reconstruction phase, since a large ...
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During natural and abnormal accidents, many people are injured, and a large number of wastes and rubbish are produced, so it is necessary to collect the injured and take them to treatment centers, which must be done in the reaction phase. Also, in the recovery and reconstruction phase, since a large amount of hazardous and non-hazardous waste is produced during accidents, effective measures should be taken to collect and recycle them if necessary. Both of these cases can be considered as a reverse logistics problem. This paper investigates reverse logistics planning in the response, improvement, and reconstruction phases in earthquake conditions. Due to the nature of the problem, it is expected that we will face a multi-objective problem, and the problem condition causes the issue of uncertainty. By increasing the dimensions of the problem, the NSGA-II meta-heuristic algorithm has been used to solve the two-objective model of the problem and the result indicates that the proposed solution algorithm works well and the quality of the answer and its solution time are appropriate. The results indicate that as capacity increases, the number of distribution centers built to meet demand decreases and the distribution center constructed may be far from some shelters, leading to increased transportation costs. According to the mentioned issues, this research uses reverse logistics in the response and recovery phases. Also, information about Tehran city will be used as data for the case study.
Research Paper
Case studies in industry and services
hadi Mehrabi Sharafabadi; Mohamad Ali Movafaghpour
Abstract
The main purpose of this study is to identify the delay factors and evaluate the type ranking of delays in natural gas distribution projects. We have investigated 274 projects in Khuzestan gas company from 2015 to 2020. Projects investigated in this study included urban, rural, transmission lines, industrial ...
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The main purpose of this study is to identify the delay factors and evaluate the type ranking of delays in natural gas distribution projects. We have investigated 274 projects in Khuzestan gas company from 2015 to 2020. Projects investigated in this study included urban, rural, transmission lines, industrial pipelines, and construction. We identified 22 delay factors and categorized them into owner, contractor, and other related factors. This research shows that Most of the delay factors are related to owner causes. In addition to identifying the factors, this study also deals with the extent of their relationship. In addition to identifying the delay factors, this study also deals with the extent of their relationship. We showed that delay factors may not be independent and there is a significant association between them. These Relations clearly showed that reduction or elimination of many delay factors lead to eliminating many others. The findings of the research were validated and implemented by company experts.
Research Paper
Data mining
Mohammad Amin Rahbar
Abstract
One of the most important issues in financial, economic, and accounting matters is the phenomenon of bankruptcy and its prediction. There is presented a hybrid method of genetic algorithm and adaptive neural-fuzzy network model (ANFIS) to evaluate predicting the bankruptcy of companies listed on the ...
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One of the most important issues in financial, economic, and accounting matters is the phenomenon of bankruptcy and its prediction. There is presented a hybrid method of genetic algorithm and adaptive neural-fuzzy network model (ANFIS) to evaluate predicting the bankruptcy of companies listed on the Tehran Stock Exchange. The statistical population of this research is the successful and bankrupt manufacturing companies in Tehran Stock Exchange and in this research, there is a different way as opposed to previous and purposeful research and all companies can prevent their possible bankruptcy with accurate forecasting. In this way, the statistical population includes 136 companies consisting of bankrupt and non-bankrupt companies. In order to construct prediction models, four variables were first selected: 1. Independent sample t-test, 2. Correlation matrix (CM), 3. Step-by-step diagnostic analysis (SDA) and 4. Principal component analysis (PCA). The final financial ratios were selected from 19 financial ratios that using selected financial ratios and a hybrid model of ANFIS and genetic algorithm and the results of the proposed model and its comparison with the hybrid model of genetic algorithm and group method of data handling shows the high capability of the proposed GA-ANFIS model in bankruptcy prediction modeling and its superiority over GA-GMDH method. The results also show that the CM-GA-ANFIS model is known as the best model for predicting bankruptcy of companies listed on the Tehran Stock Exchange. The main reason for choosing the model (GA-ANFIS) is that in addition to the fact that for the first time a combination of two methods ANFIS and genetic algorithm is used to predict the bankruptcy of companies, and also in none of the studies conducted in both areas which further highlights the need for the present study.
Research Paper
production planning
ommolbanin yousefi; saeed Rezaeei Moghadam; neda hajheidari
Abstract
One of the most important decisions taken in a supply chain is the issue of aggregate production planning where a program-within a medium time-range-- is determined for optimum manufacturing of all products using shared equipment and resources. This research presents a multi-objective model that helps ...
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One of the most important decisions taken in a supply chain is the issue of aggregate production planning where a program-within a medium time-range-- is determined for optimum manufacturing of all products using shared equipment and resources. This research presents a multi-objective model that helps the decision makers to make such decisions.
The proposed model comprises four main objectives, the first one of which considers minimizing costs (including costs of manufacturing product, supplying, maintenance, inventory stock shortage, and expenditures related to man power). The second objective is defined as maximizing customers’ satisfaction. Minimizing suppliers’ satisfaction makes up the third objective and maximizing the quality of the manufactured products constitutes the fourth objective. In this model, the demand parameter is investigated under uncertain conditions; hence, other parameters influenced by this parameter are also presented under uncertain conditions occurring within three differing scenarios. This model is solved through LP- metric and the LINGO v14.0.1.55 software. At first the model is solved by means of numerical example; then it is solved by the actual data that are related to a military industry. Finally, process, variables like inventory level, overtime work hours etc, are valued with the help of closed-loop supply chain of the proposed model.
Research Paper
Performance evaluation and benchmarking
Atiyeh Sarparast; Ravil Akhmadeev
Abstract
Considering the position of free zones in the country's commercial development, the present study identifies and ranks the factors affecting the attraction of domestic and foreign investments in the development of Iran's free trade zones and is customized in Amirabad port free zone. The present ...
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Considering the position of free zones in the country's commercial development, the present study identifies and ranks the factors affecting the attraction of domestic and foreign investments in the development of Iran's free trade zones and is customized in Amirabad port free zone. The present study is in the group of descriptive-survey research in terms of applied purpose and data collection method, which used statistical tests and multi-criteria decision making (MCDM) approach. In this regard, the statistical population of the study includes all actual and potential investors and managers of economic units located in the Amirabad Behshahr Free Zone, of which 385 people were analyzed using a questionnaire. The results obtained in the present study at the second level show that the first and the most important criteria is the management issues, followed by strategic planning, infrastructure, economic policies, laws and regulations, and finally location. Next, the most important factor is related to facilities and infrastructure, followed by the existence of natural resources and public budget allocation.
Research Paper
Computational modelling
Samaneh Akbarpour; Abdollah Shidfar; Hashem Saberi Najafi
Abstract
In this article, a mathematical model of the inverse problem is considered. Basedon this model a formulation of inverse problem for heat equation is proposed.Shifted Chebyshev Tau (SCT) method is suggested to solve the inverse problem. The aim of this determined effort is to identify unknown function ...
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In this article, a mathematical model of the inverse problem is considered. Basedon this model a formulation of inverse problem for heat equation is proposed.Shifted Chebyshev Tau (SCT) method is suggested to solve the inverse problem. The aim of this determined effort is to identify unknown function and unknown control parameter of the mathematical model. In order to achieve highly accuratesolution to this problem, the operational matrix of shifted Chebyshev polynomialsis investigated in conjunction with tau scheme. To demonstrate the validity andapplicability of the developed scheme, numerical example is presented.
Review Paper
Heuristics and Metaheuristics Algorithms
Mehdi Khadem; Abbas Toloie Eshlaghy; kiamars Fathi Hafshejani
Abstract
Over the past decade, solving complex optimization problems with metaheuristic algorithms has attracted many experts and researchers.There are exact methods and approximate methods to solve optimization problems. Nature has always been a model for humans to draw the best mechanisms and the best engineering ...
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Over the past decade, solving complex optimization problems with metaheuristic algorithms has attracted many experts and researchers.There are exact methods and approximate methods to solve optimization problems. Nature has always been a model for humans to draw the best mechanisms and the best engineering out of it and use it to solve their problems. The concept of optimization is evident in several natural processes, such as the evolution of species, the behavior of social groups, the immune system, and the search strategies of various animal populations. For this purpose, the use of nature-inspired optimization algorithms is increasingly being developed to solve various scientific and engineering problems due to their simplicity and flexibility. Anything in a particular situation can solve a significant problem for human society. This paper presents a comprehensive overview of the metaheuristic algorithms and classifications in this field and offers a novel classification based on the features of these algorithms.
Research Paper
Computational Intelligence
ramin mousa; Reza Shoukhcheshm; Elham Moradizadeh; Melika Hamian; Leila Safari; Ali Karke Abadi
Abstract
The sentiment analysis is a subtask of text classification that is known as a domain dependent problem. In order to obtain an accurate classifier for a particular domain, a large labelled dataset is needed. To tackle the challenge of data scarcity in some domains, in the area of multi-domain problems, ...
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The sentiment analysis is a subtask of text classification that is known as a domain dependent problem. In order to obtain an accurate classifier for a particular domain, a large labelled dataset is needed. To tackle the challenge of data scarcity in some domains, in the area of multi-domain problems, the classifier is trained on a set of labelled data from some domains and then it is applied to the target domains. In addition, another important issue in classification-based approaches in order to reach the better performance is that the nature of train and test data should be similar. So, a model trained by data from a specific domain, leads to poor results when it comes to another domains. This paper proposes three Weighted(deep)Neural Networks Ensemble approaches for multi-domain sentiment classification to address the mentioned issues, by training individual deep learning models (including CNN, LSTM and Bi-GRUCapsule) on specific domains. Using a weighted score of DBD and the initial polarity of the sample test data on each domain, a new aggregated score of final polarity is obtained. The DRANZIERA protocol is used for evaluation of the proposed models. The results have shown more than 0.03 improvements in average accuracy in comparison to the other state-of-the-art approaches.
Research Paper
Supply chain management
Jaber Ghanbari; Ebrahim Abbasi; Hosein Didekhani; Majid ashrafi
Abstract
The present study investigated the role of strategic cost management as a moderating variable on the relationship between supply chain practices, top management support, and financial performance improvement. Financial performance improvement was considered as a dependent variable, while supply chain ...
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The present study investigated the role of strategic cost management as a moderating variable on the relationship between supply chain practices, top management support, and financial performance improvement. Financial performance improvement was considered as a dependent variable, while supply chain practices, strategic cost management, and top management support were taken as the main independent variables. Besides, the financial structure and the firm size were considered as control variables. The research sample included 165 companies that were selected using random sampling from among companies listed on the Tehran Stock Exchange. The data were collected using the Senior Management Survey (SMS) to measure supply chain practices, top management support, and strategic cost management. The results of the structural equation modeling after discriminant tests showed that strategic cost management had a positive and significant effect on the relationship between different subscales of supply chain practices and different measures of financial performance improvement. The results also showed that the relationship between strategic cost management, senior management support, supply chain activities and improving financial performance is non-linear and so that supply chain integration is more effective at low and medium levels and at higher levels. The above has a lesser or even negative effect.
SI:RSSCMMA
Supply chain management
Somayeh Sazegari; sayyed mohammad reza davoodi; Alireza Goli
Abstract
Today, most supply chains are moving towards green business with a greater focus on environmental protection as a competitive advantage. Among them, the design of a three-stage green supply chain with optimal allocation, a multiple supply chain that includes supplier (first stage), manufacturer (second ...
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Today, most supply chains are moving towards green business with a greater focus on environmental protection as a competitive advantage. Among them, the design of a three-stage green supply chain with optimal allocation, a multiple supply chain that includes supplier (first stage), manufacturer (second stage) and distributor (third stage), based on maximum efficiency and considering the internal processes and products between these three levels, can be of special importance; Because, it will increase the economic and environmental performance of the supply chain. One of the methods used to evaluate efficiency in green supply chain management is data envelopment analysis (DEA). Therefore, performance evaluation is vital for companies to improve the effectiveness and efficiency of the supply chain. In this study, using the three-stage approach of data envelopment analysis, the data collected in 2020 from 9 Selected home appliance companies have been analyzed. The results show that Company 1 has the best efficiency and the greenest supply chain and Company 7 has the worst value of efficiency, which makes it necessary to pay more attention to low performance companies. In order to show the capability of the proposed model, the developed model was compared with its equivalent base model, and companies 1 and 2 were identified as inefficient in the proposed model, but identified as efficient in the base model. Given that the efficiency score in the proposed model is always lower than the base model, so the accuracy of the developed model can be concluded.
Research Paper
Quality Control
Duy Duong-Tran; Romina Dastoorian; Lee Wells
Abstract
Exponential Weighted Moving Average (EWMA) control charts have been widely used in Statistical Process Control to detect small and persistent process shifts. In theory, EWMA control limits monotonically increase over time to account for the continual growth of the EWMA statistic’s variance. However, ...
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Exponential Weighted Moving Average (EWMA) control charts have been widely used in Statistical Process Control to detect small and persistent process shifts. In theory, EWMA control limits monotonically increase over time to account for the continual growth of the EWMA statistic’s variance. However, these control limits are often assumed constant and are set to their respective asymptotic limits to simplify the process of applying and analyzing EWMA control charts. One-sided EWMA charts are often implemented when it is only desirable to detect shifts in a specific direction. When using one-sided EWMA charts, reflecting boundaries (resets) can be used to prevent the statistic from drifting too far from the chart’s control limit, which can delay shift detection. There have been several research efforts into designing and studying the performance of one-sided EWMA charts with reflecting boundaries. However, these efforts have maintained the constant control limit assumption. When implementing a reflecting boundary, the EWMA statistic’s variance is constantly being reset to zero, which may significantly affect the constant control limit assumption’s validity. The focus of this paper is to understand behavior of the one-sided EWMA control charts with constant and time-varying limit assumption through simulation studies.
SI: RAIDSCM
Supply chain management
Mona Beiranvand; Sayyed mohammad reza Davoodi
Abstract
Today, one of the topics in supply chain management is "multiple sales channels" and "pricing". In this research, a food producer (west Sahar Dasht Company) has been selected, and several retailers and wholesalers have been considered as the company's customers. This research ...
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Today, one of the topics in supply chain management is "multiple sales channels" and "pricing". In this research, a food producer (west Sahar Dasht Company) has been selected, and several retailers and wholesalers have been considered as the company's customers. This research dynamically solves the model through the game theory method. To obtain the equilibrium point and Stockelberg, the lower level optimal values (retailers and suppliers) are calculated based on the higher-level values (manufacturer), which turns the multi-level model into a single-level model to calculate the higher level optimal values. By presenting a case study and analyzing the sensitivity of the parameters, it was shown that some changes in the parameters have a significant effect on the problem variables, and its equilibrium model is better. Because game theory is proposed to solve problems on a small scale, and because the present problem is so complex, genetic algorithm meta-heuristic and particle aggregation optimization have been used to solve medium and large problems. To validate their results, they are compared with the results obtained from the mathematical model. Finally, comparing the performance of the two meta-heuristic algorithms through statistical analysis has shown that the particle aggregation optimization algorithm performs better than the genetic algorithm.
Research Paper
Neural Networks
Mohammad Karimi Moridani; Atiye Hajiali
Abstract
In recent years, the use of intelligent methods for automatic detection of sleep stages in medical applications to increase diagnostic accuracy and reduce the workload of physicians in analyzing sleep data by visual inspection is one of the important issues. The most important step for the automatic ...
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In recent years, the use of intelligent methods for automatic detection of sleep stages in medical applications to increase diagnostic accuracy and reduce the workload of physicians in analyzing sleep data by visual inspection is one of the important issues. The most important step for the automatic classification of sleep stages is the extraction of useful features. In this paper, an EEG-based algorithm for automatic detection of sleep stages is presented using features extracted from the recurrence plot and artificial neural network. Due to the non-stationary of the EEG signal, the recurrence plot was used in this paper for nonlinear analysis and extraction of signal features. Various extracted features have different numerical ranges. Normalization was performed to prevent the undesirable effects of large values of data. As all normalized features could not correctly classify different stages of sleep, effective features were selected. The results of this paper show the selected features and the multi-layer perceptron (MLP) neural network able to achieve the values of 98.54 ± 1.88%, 99.03 ± 1.43%, and 98.32 ± 2.11%, respectively, for specificity, sensitivity, and accuracy between the two types of sleep, i.e., Non-Rapid Eye Movement (Non-REM) and Rapid Eye Movement (REM). Also, the results show that the selection of Pz-Oz channel compared to Fpz-Cz channel leads us to a higher percentage for the separation of stages I-IV, awake, while the separation of REM stage using Fpz-Cz channel is better. The results show that the proposed method has a higher success rate in classifying sleep stages than previous studies. The proposed method could well identify and distinguish all stages of sleep at an acceptable level. In addition to saving time, automatic analysis of sleep stages can help better and more accurate diagnosis and reduce physicians' workload in analyzing sleep data through visual inspection.
Research Paper
Management and Entrepreneurship
Reza Haji Ali Beygi; Seyed Mahmoud Hashemi; Abdollah Naami
Abstract
The present study aims at presenting a model of cross-buying behavior of electronic service customers in Shahr Bank. This research is applied in terms of objective and survey-exploratory in terms of approach. The statistical population of this study consisted of a group of experts including senior managers ...
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The present study aims at presenting a model of cross-buying behavior of electronic service customers in Shahr Bank. This research is applied in terms of objective and survey-exploratory in terms of approach. The statistical population of this study consisted of a group of experts including senior managers of Shahr Bank, professors and marketing consultants familiar with the banking industry which in-depth interviews were conducted with them. The selection of experts and doing interviews with them continued until the theoretical saturation was reached and then stopped. Purposive sampling method was used in this study. 9 interviews were conducted in total. This research has been done in the period of October 2020 to May 2021. Due to using the data foundation theory in this research, the main data collection tool was unstructured in-depth interviews with experts. Finally, after three open, axial and selective kinds of coding, the conceptual model of the research was designed based on a paradigm model. In this research and according to the identified goals and categories, the category of Motivating to use various electronic services of Shahr Bank was considered as the main and axial category. This means that the core of the conceptual model is the users' motivation and inner desire to use various electronic services of this bank.
Review Paper
Case studies in industry and services
Yayan Saputra; Fibi Eko Putra; Taufik Hidayat
Abstract
The number of pipeline construction industry and electricity prices in Indonesia from 2013 to 2019 has increased. In order for the pipeline construction industry to be sustainable and competitive, the industry must strive to reduce electricity consumption, one of which is the ISO 50001 energy management ...
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The number of pipeline construction industry and electricity prices in Indonesia from 2013 to 2019 has increased. In order for the pipeline construction industry to be sustainable and competitive, the industry must strive to reduce electricity consumption, one of which is the ISO 50001 energy management system approach. This research identifies energy intensity data; energy performance data from significant energy use in the production process of the pipeline construction industry and comparing it with baseline values; targets to be achieved; and analyzing the effects of machines, materials, methods, human and environmental factors on energy consumption. Based on the results of the discussion, this research can conclude that the construction of piping work requires electricity for the cutting and welding process. The highest electrical intensity intensity is in the welding process, which averages 16.4 KJ/cm (88.2% of total energy consumption) and the cutting process is 2.2 KJ/cm (11.8% of total energy consumption). So a significant use of energy for corrective action is that the pipe work process is a welding process. Factors that cause high energy consumption/energy intensity in pipe construction work include method and material factors. Result of every factors can reduce the electricity consumption of the welding process from 16.4 KJ/cm to 7.5 KJ/cm (54.3%).
Research Paper
Operations Research
Seyed Amin Badri; Negar Yarmohamadi
Abstract
The aim of this paper is to propose a mathematical model for two dental centers in a competitive market of dental tourism. Dental tourists are looking for cheaper treatment with proper quality, and dental centers are looking to maximize their profits by providing services to tourists. Government also ...
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The aim of this paper is to propose a mathematical model for two dental centers in a competitive market of dental tourism. Dental tourists are looking for cheaper treatment with proper quality, and dental centers are looking to maximize their profits by providing services to tourists. Government also monitors dental centers by setting tariffs (subsidies or taxes). This problem is modeled and solved in the form of Stackelberg (or Leader-Follower) Game. The government as the leader determines the amount of tariffs and then the dental centers as the followers simultaneously determine the price and quality level of their services. To solve the game, first the equilibrium values related to the price and quality level of the services of the dental centers have been calculated by Nash equilibrium. Then, according to the equilibrium values obtained for dental centers, the optimal amount of tariffs are calculated. Finally, to clarify the proposed model a numerical example is provided and sensitivity analysis is performed on some parameters. In this paper, for the first time a mathematical model is developed for pricing and determining the quality of services in a competitive market of dental tourism. The obtained results indicate that increasing the amount of subsidy will lead to a decrease in the prices of service provided by the dental centers. Moreover, by increasing the amount of subsidies allocated to the dental centers, the government can expand the dental tourism industry.
Research Paper
Supply chain management
Meysam Donyavi Rad; Ehsan Sadeh; Zeinolabedin Amini Sabegh; Reza Ehtesham Rasi
Abstract
The natural disasters of the last few decades clearly reveal that natural disasters impose high financial and human costs on governments and communities. Concerns in this regard are growing day by day. Making the right decisions and taking appropriate and timely measures in each phase of the crisis management ...
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The natural disasters of the last few decades clearly reveal that natural disasters impose high financial and human costs on governments and communities. Concerns in this regard are growing day by day. Making the right decisions and taking appropriate and timely measures in each phase of the crisis management cycle will reduce potential damage at the time of the disaster and reduce the vulnerability of society. Therefore, in this research, a mathematical model of crisis logistics planning considering the problem of primary and secondary crisis in disaster relief is introduced, which is the innovation of this research. In the primary crisis, the goal is to provide services and relief goods to crisis areas, and in the second stage, the secondary crisis that occurs after the primary crisis seeks to provide relief to crisis centers and transfer the injured to relief centers. Therefore, this research proposes a mathematical fuzzy ideal programming model in two primary and secondary crises. In the primary crisis, the goal is to provide services and relief goods to crisis-stricken areas. The secondary crisis, which occurs after the primary crisis, aims to support crisis-stricken centers and move injured people to relief bases in the second step. According to the proposed model, Bertsimas-Sim’s fuzzy programming that formulation proposed by Bertsimas and Sim (B&S) [1] and robust approach we initially used. The Epsilon constraint method was used to solve the low-dimensional model. Multi-objective meta-heuristic algorithms have been designed to handle the computational complexity of large-scale real-time problems. Multiple comparisons and analyses have been proposed to assess the performance of the model and problem-solving capabilities. The results indicate that the proposed approach can be applied and implemented to develop a real-world humanitarian logistics network.
Research Paper
Forecasting, production planning, and control
Ejiroghene Kelly Orhorhoro
Abstract
In this study, the effects of corrosion rate on post welded annealed heat-treated medium carbon steel in seawater was investigated. The medium carbon steel samples were butt-welded by using the shielded metal arc welding technique and, afterwards, heat treated by annealing at different annealing temperature ...
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In this study, the effects of corrosion rate on post welded annealed heat-treated medium carbon steel in seawater was investigated. The medium carbon steel samples were butt-welded by using the shielded metal arc welding technique and, afterwards, heat treated by annealing at different annealing temperature was carried out. The microstructure of the unwelded and post welded heated samples was characterised by means of optical microscopy. The as received (control), unwelded and post welded annealed medium carbon steel samples were immersed in sea water for a duration of one hundred (100) days, and this was to stimulate the effect on equipment in offshore and food processing applications. Post welded heat treatment on the microstructure, weight loss and corrosion rate were evaluated. The results obtained showed an initial increase in both the weight loss and corrosion rate of samples up to 40 days and started decreasing afterwards. It was equally observed that the post welded annealed samples showed more corrosion activities than the un-welded annealed samples. Above and beyond, corrosion activity was more prominent in samples with the highest annealing temperature. More so, the unwelded annealed medium carbon steel showed a dispersion of coalescence cementite and ferrite grain while the post welded annealed medium carbon steel samples showed a martensite (light area marked by arrows) distributed in the ferrite (dark area) matrix.
Research Paper
Manufacturing and Logistics
Robert S Keyser; Renee S. Severin; Matthew J. Geiger
Abstract
The Single-Minute Exchange of Dies (SMED) methodology proved an effective approach for reducing setup times on a bottleneck 66” Koppers rotary die-cutter machine center in a corrugated box plant. Root cause analysis techniques, such as a check sheet and control charts, aided the analysis. The supervisor ...
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The Single-Minute Exchange of Dies (SMED) methodology proved an effective approach for reducing setup times on a bottleneck 66” Koppers rotary die-cutter machine center in a corrugated box plant. Root cause analysis techniques, such as a check sheet and control charts, aided the analysis. The supervisor and work crew, consisting of both the operator and setup person, played an integral role in reducing setup times by consenting to being videotaped during a typical setup and then breaking down the video to distinguish internal versus external steps. By converting many internal steps to external steps, average setup times were reduced from 55 minutes to 32 minutes, a 42% improvement.
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