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
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.
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.
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.
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
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.
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
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
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
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.
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 Fare ...
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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
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 study ...
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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.
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 dynamically solves the model ...
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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
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
Mathematical modelling
Mohsen Khasteh; Amir Hossein Refahi Sheikhani; Farhad Shariffar
Abstract
In this paper, we proposed a numerical approach to solve a distributed order time fractional COVID 19 virus model. The fractional derivatives are shown in the Caputo-Prabhakar contains generalized Mittag-Leffler Kernel. The coronavirus 19 disease model has 8 Inger diets leading to system of 8 nonlinear ...
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In this paper, we proposed a numerical approach to solve a distributed order time fractional COVID 19 virus model. The fractional derivatives are shown in the Caputo-Prabhakar contains generalized Mittag-Leffler Kernel. The coronavirus 19 disease model has 8 Inger diets leading to system of 8 nonlinear ordinary differential equations in this sense, we used the midpoint quadrature method and finite different scheme for solving this problem, our approximation method reduce the distributed order time fractional COVID 19 virus equations to a system of algebraic equations. Finally, to confirm the efficiency and accuracy of this method, we presented some numerical experiments for several values of distributed order. Also, all parameters introduced in the given model are positive parameters.
Research Paper
Game theory
Elham Sadat Mousavi; Ashkan Hafezalkotob; Ahmad Makui; Mohammad Kazem Sayadi
Abstract
This paper presents an optimization model for hotel pricing in the competitive environment following the Covid-19 epidemic, in which the government intervenes by offering appropriate tariffs and hotels use incentive policies such as discounts to attract customers. we consider the government as the leader ...
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This paper presents an optimization model for hotel pricing in the competitive environment following the Covid-19 epidemic, in which the government intervenes by offering appropriate tariffs and hotels use incentive policies such as discounts to attract customers. we consider the government as the leader and the hotels as the followers of the Stalkberg model, then apply the Nash equilibrium to determine the optimal price and demand of hotels in competitive conditions, taking into account the discount. By considering a government utility function, the optimal level of government tariffs is determined. The results indicate that government intervention in the tourism industry includes measures that benefit tourism. Because the government can increase the hotel revenue and expand tourism in favor of hoteliers by reducing its profits. Extensive analysis has been performed on five-star, four-star, and three-star hotels in a tourist area in Iran, and some of the most important managerial insights have been explained.
Research Paper
Case studies in industry and services
AYYAPPAN - S
Abstract
To enhance the manufacturing process capability of a refractory company, the scope for implementing the Lean Six Sigma (LSS) methodology is analyzed in this work. The DMAIC methodology of Six Sigma is used in this project to determine the Critical to Quality Characteristics (CTQs), defining the possible ...
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To enhance the manufacturing process capability of a refractory company, the scope for implementing the Lean Six Sigma (LSS) methodology is analyzed in this work. The DMAIC methodology of Six Sigma is used in this project to determine the Critical to Quality Characteristics (CTQs), defining the possible causes, identifying the variation in sources, establishing the variable relationships, and implementing the control plans. It was found from the DMAIC approach that the quality of Raw Crude, Water Content, and the frequency of using Temperature Calibration Equipment are the main factors responsible for lowering Productivity in Shaft Kiln. To improve the productivity of Kiln, it was suggested to process the raw crude free of mud, remove the moisture content present in the magnesite stones and take action on changing the frequency of measuring the oil feeding calibration equipment.
SI:RSSCMMA
Risk management
Mohammad Reza Alijanzadeh; Seyed Ahmad Shayannia; Mohammad Mehdi Movahedi
Abstract
One of the methods that has been widely used by researchers in analyzing the risk of net operations is the analysis of the effect and failure modes in order to identify critical failure modes and focus planning and net resources on them. In analyzing the effect and failure modes, one of the most important ...
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One of the methods that has been widely used by researchers in analyzing the risk of net operations is the analysis of the effect and failure modes in order to identify critical failure modes and focus planning and net resources on them. In analyzing the effect and failure modes, one of the most important steps is the process of prioritizing the equipment in order to determine the critical equipment, as well as determining the critical failure modes and prioritizing them in order to purposefully plan the net operation. The purpose of this paper is to dynamically rank equipment in intuitive fuzzy environments with interval values in order to identify and prioritize critical equipment and to present a mathematical model for combining optimization of preventive maintenance intervals and control parameters. For this purpose, a model is presented that calculates the dynamic weights of each equipment according to the conditions of each equipment in the indicators of failure probability, failure consequence and lack of fault detection power, and therefore dynamic ranking is provided for the equipment. In this research, for dynamic prioritization of equipment, the method of analysis of the ratio of intuitive fuzzy gradual weighting with quantitative values (IVIF-SWARA) was presented. Then, a mathematical model was presented for the identified critical equipment. The proposed model can determine the optimal value of each of the four decision variables, ie sample size, inspection rotation time, control limit coefficient and preventive repair intervals of each of the critical equipment of the Northern Oil Pipeline and Telecommunication Company and the total expected cost of integration per unit. Minimize time. The results show that the proposed model is much more flexible in calculating the weight and dynamic rating of equipment and provides more logical rating results.
Research Paper
Quality Control
Chimata Murali Krishna; Satyam Sahu; Mayank M Kisnya; Gunwant M Mishra; Samyak M Jain
Abstract
The objectives of this work are to investigate the status of implementation of quality initiatives by manufacturing firms in Madhya Pradesh, India, and to compare large and small-medium scale industries. Very few researchers have attempted to compare large scale and small-medium scale firms in order ...
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The objectives of this work are to investigate the status of implementation of quality initiatives by manufacturing firms in Madhya Pradesh, India, and to compare large and small-medium scale industries. Very few researchers have attempted to compare large scale and small-medium scale firms in order to know the extent of implementation of quality initiatives for a state like Madhya Pradesh. In this study, the survey questionnaire method was used for the collection of data. Nine quality initiatives were selected for the study. The obtained data are grouped into two groups, viz., (i) large scale firms, and (ii) small-medium scale firms. Descriptive and inferential statistics are used for analysis and the results are presented. Hypothesis testing was used to investigate for any significant difference between the two groups of firms in implementing each quality initiative. Results from inferential statistics reveal that there is a significant difference in the implementation of quality initiatives in large and small-medium scale industries. The findings of the present work will guide firms to identify areas where improvement is required at each quality initiative level. The study will help small-medium scale firms in the Madhya Pradesh state of India to conduct training programs in the areas of relevant quality initiatives for improving their quality of products.
Research Paper
Case studies in industry and services
Robert S Keyser; Parisa Pooyan
Abstract
Root cause analysis techniques are often applied to problems in the workplace; however, they may also prove very useful to home projects. This research explores the application of two root cause analysis techniques in home projects: (1) 5 Whys to determine the root cause of a home air conditioning unit ...
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Root cause analysis techniques are often applied to problems in the workplace; however, they may also prove very useful to home projects. This research explores the application of two root cause analysis techniques in home projects: (1) 5 Whys to determine the root cause of a home air conditioning unit that runs continuously but does not cool, and (2) an innovative Lean PFMEA to repair a John Deere riding mower that starts, then stops. Employing the 5 Whys technique led to the discovery of incorrect color-coded wiring from the original air conditioning unit to the thermostat. Lean PFMEA enabled a correct diagnosis and resolution of the mower start/stop issue via a Kaizen event, grass clippings in the fuel line, which was remedied by cleaning the fuel tank and replacing the fuel lines, fuel filter, and carburetor. These techniques provide Lean methodological approaches to problem-solving, which often leads to reduced homeowner aggravation, repair time, and repair expense.
Research Paper
Human factors, ergonomics, and safety
Silas Oseme Okuma; Akpofure Avwerosuoghene Enughwure
Abstract
The purpose of this research is to investigate the safety of inland waterway transportation in Kurutie, Okerenkoko, and Escravos River, Nigeria. The study used a cross-sectional research design, and the study's target group includes passengers who are technical experts, maritime workers, non-academic, ...
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The purpose of this research is to investigate the safety of inland waterway transportation in Kurutie, Okerenkoko, and Escravos River, Nigeria. The study used a cross-sectional research design, and the study's target group includes passengers who are technical experts, maritime workers, non-academic, academic personnel's and students of Nigeria Maritime University, and self-employed passengers who live in the study locations. Questionnaires and field observations were used to obtain data. 378 questionnaires were delivered throughout the study area. According to the study, most cases of maritime boat mishaps beleaguered the inland waterway in the study area due to unskilled boat drivers, overloading/overcrowding of boats, and a lack of enforcement of safety laws by government agencies within the study area. The study recommended that relevant authorities, such as the Nigeria Inland Waterways Authority, enforce safety regulations among jetty operators and boat drivers; that training and certifying boat drivers are enforced; and that government involvement be increased by developing a sensitization program to educate passengers on the importance of adhering to safety practices along the waterways.
Research Paper
Management and Entrepreneurship
Seyedeh Sara Pourmorshed; Seyed Mojtaba Sajadi; Sonia Sadeghian Esfahani
Abstract
This paper aims to introduce a business model for eco-tourism residences based on Osterwalder’s canvas business model with a creative tourism approach. Despite the significance of creative tourism and business model of eco-tourism residences, there is still a lack of sufficient attention to these ...
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This paper aims to introduce a business model for eco-tourism residences based on Osterwalder’s canvas business model with a creative tourism approach. Despite the significance of creative tourism and business model of eco-tourism residences, there is still a lack of sufficient attention to these issues in the literature. Moreover, regarding the growing tourism industry in Iran and the importance of creative tourism in cultural and adventure tourism, it is necessary to seek new ideas to improve service quality and the business owners’ knowledge of their industry. In this regard, this multiple case study research is conducted by semi-structured interviews with seven eco-tourism residence owners in Iran. Open and axial coding methods were adopted for data analysis. This research identifies the main components of nine blocks of Osterwalder’s canvas business model for eco-tourism residences, including, value proposition, customer segments, customer relationships, channels, key resources, key activities, key partners, revenue streams, and cost structure. The results of this study show that the supply factors of creative tourism framework including diversity of world cultures, the provision of unique culture, infrastructure, local crafts, hospitality, creative industries, cultural tourism resources, and more types of tourism are connected to the value propositions in the presented business model.
Research Paper
Data Envelopment Analysis, DEA
Reza Fallahnejad; Sanaz Asadi Rahmati; Kayvan Moradipour
Abstract
To evaluate the performance and estimate the efficiency of decision-making units (DMUs) in Data Envelopment Analysis (DEA), the available data are used. These data are usually divided into two categories of inputs and outputs based on their natures. If the price data is also available for inputs, it ...
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To evaluate the performance and estimate the efficiency of decision-making units (DMUs) in Data Envelopment Analysis (DEA), the available data are used. These data are usually divided into two categories of inputs and outputs based on their natures. If the price data is also available for inputs, it is necessary to calculate another type of the efficiency called cost effi-ciency. Since the efficiency of units in such a framework is depended on the both quantities of inputs and outputs and also the prices of inputs, it is important to find the sources of cost inefficiency related to each of the factors and plans to ad-dress them. In this paper, we intend to present a new decomposition of cost efficiency and observed cost versus optimal cost, which are arised from each of the factors involved in the cost inefficiency, in a non-competitive pricing environment which the input price vector for different DMUs can be different. Moreover, for the first time, in parallel with using the PPS based on input and output quantities and introducing some cost inefficiency factors related to this set, we will intro-duce new sets called price and cost production sets that the first is based on the prices of inputs and output factors, and the second is based on the optimal vectors of inputs and prices obtained from two previous PPS, and then we will introduce other factors of cost inefficiency in the sets. Accordingly, new decomposition for cost inefficiencies will be presented. Also, in the previous analyzes, congestion inefficiency has not been considered as one of the important factors in cost inefficiency. In this study, we also intend to consider the impact of this factor on cost efficiency.
Research Paper
Decision analysis and methods
Elham Ebrahimi; Mohammad Reza Fathi; Seyed Mohammad Sobhani
Abstract
Multiple criteria decision-making (MCDM) is well known nowadays as a methodology in which a set of techniques are integrated to evaluate a set of alternatives with specified criteria for the purpose of selecting or ranking. The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is ...
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Multiple criteria decision-making (MCDM) is well known nowadays as a methodology in which a set of techniques are integrated to evaluate a set of alternatives with specified criteria for the purpose of selecting or ranking. The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is well-established methodology frequently considered in MCDM analyses. TOPSIS has a sound logic that represents the rationale of human choice and is a scalar value simultaneously taking into account both the best and worst alternatives. Moreover, it has a simple computation process that could be easily programmed and finally it has the ability to rank alternatives on attributes to be visualized on a polyhedron, in at least two dimensions. Despite the advantages of this method, the process of ranking alternative according to related criteria may need more consideration. Typically, there are contributions in this article. First, a new similarity measure has been introduced followed by a modification applied to TOPSIS analyses. Second, the modified similarity technique was subsequently extended in the fuzzy context to cope with the uncertainty inherently existing in human judgments. A numerical example of the personnel selection was presented to demonstrate the possible application of the proposed method in human resource management. The outcome of applying fuzzy similarity method showed a significant distinction in ranking alternatives compered to TOPSIS method. Therefore, the modification is sound to be a proper solution.
Research Paper
Case studies in industry and services
Seyed Farid Mousavi; Arash Apornak; Mohammadreza Pourhassan
Abstract
Although the importance of supply chain agility considering the necessity of speed of action, response to customers, progressive changes in the market, consumers’ needs, etc. in many industries is clear both scientifically and experimentally, today organizations have found that the ...
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Although the importance of supply chain agility considering the necessity of speed of action, response to customers, progressive changes in the market, consumers’ needs, etc. in many industries is clear both scientifically and experimentally, today organizations have found that the benefit from this cooperation is greater than cases performed without collaboration with relevant organizations. Meanwhile, supply chain management refers to integration of all processes and activities in the supply chain through improving the relations and implementing the organizational processes in order to achieve competitive advantages. On the other hand, uncertainty in the supply chain results in non-optimality of decisions that are made with assumption of certainty. Accordingly, the main aim of this research is to provide a model for supply chain in an agile and flexible state based on uncertainty variables. The method of research has been based on a mathematical model, whose stages of implementation are investigated by breaking down this model step-by-step. For this purpose, in the first stage and after getting familiar with the intended modeling industry, solution and simulation were done. Eventually the results were compared indicating that through reducing the risk-taking (increasing the protection levels), the objective function which was of minimization type worsened. This study also showed that model robustification is very important in order to reduce the risk of decision-making.
Research Paper
Engineering Modeling
Alireza Hamidieh; salar babaei
Abstract
The development of cell sites as part of the infrastructure of telecommunication technology is playing a unique role in emerging businesses at present. Natural disasters and crises can disrupt communication equipment and create severe challenges in service provisions, especially health and security, ...
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The development of cell sites as part of the infrastructure of telecommunication technology is playing a unique role in emerging businesses at present. Natural disasters and crises can disrupt communication equipment and create severe challenges in service provisions, especially health and security, by damaging sites. This might lead to traffic congestion in certain network sections, causing chaos and social crises and increasing the commissioning and equipping costs of backup sites for operators. This study developed an integrated location–coverage–allocation model to improve sustainability through maximum coverage, enhanced flexibility, and minimized overhead expense by determining the position of backup sites and mitigating environmental pollutions resulting from the establishment of sites. The stochastic robust optimization model was employed to control the effect of nonparametric uncertainty, while acceptable solutions were generated using the Lagrangian relaxation to address complicated model constraints.
SI:RSSCMMA
Supply chain management
Peiman Ghasemi; Hossein hemmaty; Adel Pourghader chobar; Mohamad Reza Heidari; Mahdi Keramati
Abstract
Today, logistics costs often make up a major part of large organizations’ expenses. These costs can be reduced with optimal design and its implementation in the supply chain. As a result, in present study, a two-objective mathematical location-routing model is presented, where an objective is to ...
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Today, logistics costs often make up a major part of large organizations’ expenses. These costs can be reduced with optimal design and its implementation in the supply chain. As a result, in present study, a two-objective mathematical location-routing model is presented, where an objective is to minimize the costs and the next is to maximize the reliability in order to deliver the goods timely to customer according to the probable time and time window. The proposed problem has two levels of distribution. The first level, which is called transportation level, points to the distribution of products from a factory to an open distribution center, and the latter is known as routing level, which is related to a part of the problem in which we deliver products from the warehouse to customers. The proposed mathematical model is solved by Epsilon-constraint and NSGA-II approaches in small and medium, and large scales problem, respectively. The present study has provided the following contributions: concurrent locating and routing in the supply chain in accordance with the customer’s time window, probable travel time in the supply chain and customer’s reliability in the supply chain. The assessment metric results indicate the proper performance of our proposed model.
Research Paper
Customer Satisfaction and Loyalty
reza yazdani; Mohammad Javad Taghipourian; Mohammad Mahdi Pourpasha; Seyed Shamseddin Hosseini
Abstract
In the last decade, information and communication technology (ICT) was used as the most effective tool to help businesses gain a competitive advantage by attracting customers. Thus, ICT has significantly contributed to the growth of e-commerce. Internet access allows e-commerce to spread globally and ...
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In the last decade, information and communication technology (ICT) was used as the most effective tool to help businesses gain a competitive advantage by attracting customers. Thus, ICT has significantly contributed to the growth of e-commerce. Internet access allows e-commerce to spread globally and cheaply. However, many organizations did not realize the potential value created by e-commerce. Since the provision of information and branding at the destination necessarily involves the focused attention of all tourism companies in the destination, e-commerce can lead to the development of a new distribution channel in a virtual network and connects the producer with the customer. To this end, the present study analyzed the factors affecting brand strengthening drivers in e-commerce in the Iranian tourism industry. Brand strengthening drivers were ranked using Shannon’s entropy method. The results indicated that advertising and brand communication are the most effective brand strengthening drivers.
Research Paper
Data Envelopment Analysis, DEA
Maryam Arbabi; Zohreh Moghaddas; Alireza Amirteimoori; Mohsen Khunsiavash
Abstract
Sensitivity analysis in optimization problems is important for managers and decision-makers to introduce different strategies. Data envelopment analysis is a method based on mathematical programming to evaluate the efficiency of a set of decision-making units. Due to the importance of sensitivity analysis ...
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Sensitivity analysis in optimization problems is important for managers and decision-makers to introduce different strategies. Data envelopment analysis is a method based on mathematical programming to evaluate the efficiency of a set of decision-making units. Due to the importance of sensitivity analysis in an optimization problem, the development of a data envelopment analysis model called inverse model in data envelopment analysis is presented. The purpose of this model is to analyze the sensitivity of some inputs or outputs to changes in some other inputs or outputs of the unit under evaluation, provided that the amount of efficiency remains constant or improves at the discretion of the manager. In this research, for the first time, we introduce the inverse model in data envelopment analysis with network structure. In fact, we examine the extent to which the input parameters are likely to change based on the presuppositions of the problem, for the output changes that are applied as the manager desires. One of the key points of this research is that to make the modeling more consistent with reality, the leader-follower method was used in estimating the parameters in the network. In addition, the opinions of the system manager and the decision-maker, who have full control over the system under their management, are included in this modeling to estimate the desired values. Another feature of this modeling is the consideration of uncontrollable factors in the inverse model in data envelopment analysis with network structure. Finally, using a numerical example, the results obtained are analyzed based on the proposed model.
Research Paper
Fuzzy optimization
Elham Hosseinzadeh; Javad Tayyebi
Abstract
Neutrosophic set theory plays an important role in dealing with the impreciseness and inconsistency in data encountered in solving real-life problems. The current paper focuses on the neutrosophic fuzzy multiobjective linear programming problem (NFMOLPP), where the coefficients of the objective functions, ...
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Neutrosophic set theory plays an important role in dealing with the impreciseness and inconsistency in data encountered in solving real-life problems. The current paper focuses on the neutrosophic fuzzy multiobjective linear programming problem (NFMOLPP), where the coefficients of the objective functions, constraints, and right-hand side parameters are single-valued trapezoidal neutrosophic numbers (NNs). From the viewpoint of complexity of the problem, a ranking function of NNs is proposed to convert the problem into equivalent MOLPPs with crisp parameters. Then suitable membership functions for each objective are formulated using their lowest and highest value. With the aim of linear programming techniques, a compromise optimal solution of NFMOLPP is obtained. The main advantage of the proposed approach is that it obtains a compromise solution by optimizing truth-membership, indeterminacy-membership, and falsity-membership functions, simultaneously. Finally, a transportation problem is introduced as an application to illustrate the utility and practicality of the approach.
Research Paper
Data Envelopment Analysis, DEA
Sima Madadi; Farhad Hosseinzadeh Lotfi; Mehdi Fallah Jellodar; Mohsen Rostamy-Malkhalifeh
Abstract
We developed a DEA-based resource re-allocation model based on environmental DEA technology for organizations with a central decision-making environment. The proposed model considered a weak disposability axiom for undesirable outputs and combined data envelopment analysis (DEA) with multiple-objective ...
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We developed a DEA-based resource re-allocation model based on environmental DEA technology for organizations with a central decision-making environment. The proposed model considered a weak disposability axiom for undesirable outputs and combined data envelopment analysis (DEA) with multiple-objective programing (MOP). The objective was to find the appropriate re-allocation model in order to save energy and reduce environmental pollution, so that the next steps could be taken toward improvement. Given that reducing the inputs and outputs of inefficient units is sometimes not achievable and does not seem logical, for the reduction in the values to be logical and achievable, we divided the decision-making units (DMUs) into different levels of efficient frontier using the context-dependent DEA technique. For this purpose, the model was designed to move the DMUs from the current frontier to the efficient frontier of the previous layer, which has better efficiency conditions, or keep them on their own frontier. In addition, the opinion of the central decision maker regarding the amount of reduction in the inputs and outputs was expressed using Goal Programing (GP) in a way that does not make the model infeasible. By implementing the model in 8 regions of the world, suggestions were made regarding the amounts of energy saving and CO2 pollution reduction based on the conditions determined by the central decision maker aiming improve the efficiency of inefficient units in the next step.
Research Paper
Engineering Modeling
Reza Eslamipoor; Arash Nobari
Abstract
Nowadays, designing a reliable network for blood supply chains by which most blood demands can be supplied is an important problem in the health care systems. In this paper, a multi-objective model is provided to create a sustainable blood supply chain, which contains multiple donors, collection centers, ...
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Nowadays, designing a reliable network for blood supply chains by which most blood demands can be supplied is an important problem in the health care systems. In this paper, a multi-objective model is provided to create a sustainable blood supply chain, which contains multiple donors, collection centers, distribution centers, and hospitals at different echelons. Regarding the potential of a blood shortage occurring, the suggested model considers the supply chain's capacity to meet hospitals' blood demands as dependable and a means of achieving the societal purpose. In addition, limiting the overall cost and environmental effect of designing a supply network and blood transportation are considered economical and environmental objectives. To solve the proposed multi-objective model, an improved ε-constraint approach is first employed to construct a single-objective model. Additionally, an imperialist competitive algorithm is developed to solve the single-objective model. Several test cases are analysed to determine the technique's effectiveness. CPLEX is then used to compare the results.
Research Paper
Case studies in industry and services
K. M. Mustafizur Rahman
Abstract
Job satisfaction of the employees is a concerning issue, accelerates the productivity of any organization. Higher job satisfaction among the employees means the higher chance of profitability of the employers. An effective understanding of factors associated with job satisfaction of the employees is ...
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Job satisfaction of the employees is a concerning issue, accelerates the productivity of any organization. Higher job satisfaction among the employees means the higher chance of profitability of the employers. An effective understanding of factors associated with job satisfaction of the employees is precious to push organizational development. This study aims to identify the determinants of job satisfaction among the employees of aluminum industries in Rajshahi city of Bangladesh. In this study, age, sex, education, work experience, satisfaction with salary, workplace environment and workplace management system are revealed as the determinants of job satisfaction. As the first study, it provides the determinants of job satisfaction among the employees in aluminum industries in Rajshahi city of Bangladesh. Relevant authorities are suggested to consider the study’s findings and recommendations to create new policies regarding job satisfaction.
Research Paper
Game theory
Fatemeh Ghaeminasab; Mohsen Rostamy-Malkhalifeh; farhad hosseinzadeh Lotfi; Mohammad-Hasan Behzadi; Hamidreza Navidi
Abstract
In this paper, while taking into account the cooperative relationships between units, the problem of revenue allocation is considered as a coalitional game. In order for the allocation to be equitable, by relying on the concept of DEA efficiency, a new characteristic function is presented, and then using ...
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In this paper, while taking into account the cooperative relationships between units, the problem of revenue allocation is considered as a coalitional game. In order for the allocation to be equitable, by relying on the concept of DEA efficiency, a new characteristic function is presented, and then using the concept of the Shapley value, which is a well-recognized concept in coalitional game theory, a unique solution is obtained for the revenue allocation problem. And finally, to evaluate the equitability of the performed revenue allocation, the Gini coefficient is utilized. A comparison of the Gini coefficient obtained for our method with those of some existing methods showed that our method is more equitable than the previous ones. This demonstrates how impactful the wise and accurate selection of the characteristic function is in the equitability of the results.
Research Paper
Scheduling
Vahid Bahmani; Mohammad Amin Adibi; Esmaeil Mehdizadeh
Abstract
This paper provides an integrated model for a two-stage assembly flow shop scheduling problem and distribution through vehicle routing in a soft time window. So, a mixed-integer linear programming (MILP) model has been proposed with the objective of minimizing the total cost of distribution, holding ...
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This paper provides an integrated model for a two-stage assembly flow shop scheduling problem and distribution through vehicle routing in a soft time window. So, a mixed-integer linear programming (MILP) model has been proposed with the objective of minimizing the total cost of distribution, holding of products, and penalties of violating delivery time windows. To solve this problem, an improved meta-heuristic algorithm based on whale optimization algorithm (WOA) has been developed. A comparison of the integrated and non-integrated model in a case study of industrial gearboxes production shows that the integrated model compared to the non-integrated model has saved 15.6% and 13.6% in terms of delay time and total costs, respectively. Computational experiments also indicate the efficiency of improved WOA in converging to optimal solution and achieve better solution in comparison to the genetic algorithm (GA).
Research Paper
Industrial Mathematics
Ramin Barati; Sara Fanatirashidi
Abstract
This study aims to verify the main factors influencing turnover intention in the Iran hospitality industry. The objective of this study is to construct a fuzzy AHP and fuzzy TOPSIS model to evaluate the dimensions of the hotel employee turnover intention model. The performance evaluation for employee ...
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This study aims to verify the main factors influencing turnover intention in the Iran hospitality industry. The objective of this study is to construct a fuzzy AHP and fuzzy TOPSIS model to evaluate the dimensions of the hotel employee turnover intention model. The performance evaluation for employee turnover intention includes Work Itself, Supervision, Coworkers Relationship, Salary and Benefit, Career Opportunities, Job Stress, Perceived Risk, and Job Insecurity. These dimensions generate a final evaluation for ranking priority among the employee turnover intention of the proposed model. The importance of dimensions is evaluated by 20 experts, and decision-making is processed through the fuzzy concept and fuzzy environment. From the critical fuzzy AHP and fuzzy TOPSIS analysis results, the study shows that the most important dimensions of employee turnover intention in the hotel industry model are salary and benefits. Moreover, the results indicate that the least important dimensions are the Co-workers Relationship, Supervision, and Career Opportunities. The second group dimensions that impact employee turnover in the context of the COVID-19 epidemic are Work Itself, Job Stress Perceived Risk, and Job Insecurity. In addition, this study’s results show that three-star hotels have the highest value of turnover intention; the second is the Four and Five-star hotels, and the third is the Below three-star hotels. The results of the study will help businesses in the field of hospitality have a more comprehensive view of human resource management activities. Especially, this study provides implications for hotel managers in understanding employee behavior and their turnover intention during the context of the COVID-19 epidemic based on the eight proposed dimensions.
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