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
Rita de Fátima Muniz; Wagner Bandeira Andriola; Sheila Maria Muniz; Antônio Clécio Fontelles Thomaz
Abstract
The present article is an excerpt from a research published in the Journal Revista Ensaio: Avaliação e Políticas Públicas em Educação (2021). The present study adopted the Data Envelopment Analysis (DEA) methodology, to identify the weightiest factors that are ...
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The present article is an excerpt from a research published in the Journal Revista Ensaio: Avaliação e Políticas Públicas em Educação (2021). The present study adopted the Data Envelopment Analysis (DEA) methodology, to identify the weightiest 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.
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
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.
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
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.
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
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.
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
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
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
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
Industrial Mathematics
Ramin Barati; Sara Fanati Rashidi
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.
Research Paper
Performance evaluation and benchmarking
Tri Ngudi Wiyatno; Atty Tri Juniarti; Iman Sudirman
Abstract
The Floor Tiles Industry in accordance with State Regulations is one of the manufacturing industries that can participate in Indonesia into a Developed Industrial Country, supported by the availability of various technologies and product innovations so that domestic floor tiles can be accepted. In the ...
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The Floor Tiles Industry in accordance with State Regulations is one of the manufacturing industries that can participate in Indonesia into a Developed Industrial Country, supported by the availability of various technologies and product innovations so that domestic floor tiles can be accepted. In the face of increasing competition, domestic floor tiles industry trying to improve the quality of the products by implementing a strict standardization system for production processes and products produced by implementing TQM. Based on the components that influence of TQM, variables of leadership, technical competence and organizational culture are closely related to certain factors. A leadership pattern that focuses on goals or targets determined and taken based on scientific thinking by taking into account the various parties involved will improve the quality. Education and training as well as employee involvement by providing controlled independence as well as improving the technical quality.
Research Paper
Decision analysis and methods
Mehdi Soltanifar
Abstract
In this paper, a hybrid method based on a linear programming model for solving Multi-Attribute Decision-Making (MADM) problems by combining two new methods, the COmplex PRoportional Assessment (COPRAS) and the Multi-objective Optimization Ratio Analysis (MOORA) and also using the concept of discrimination ...
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In this paper, a hybrid method based on a linear programming model for solving Multi-Attribute Decision-Making (MADM) problems by combining two new methods, the COmplex PRoportional Assessment (COPRAS) and the Multi-objective Optimization Ratio Analysis (MOORA) and also using the concept of discrimination intensity functions are presented. Further interaction with the Decision Maker (DM) to determine the weights of the attributes and calculate the weights by solving a linear programming problem without determining the predetermined weight are two of the advantages of the new method. In the proposed method, for each alternative, attributes are weighted with optimism for that alternative, and then alternatives are ranked through efficiency intervals. The proposed method is implemented on a real-world problem derived from the subject literature and compared with other MADM methods. The difference in the final results is evident due to the consideration of more details in determining the rankings.
Research Paper
Engineering Optimization
Ayodeji Nathaniel Oyedeji; Ibrahim Iliyasu; James Bitrus Bello; Kazeem Adeniyi Salami; Musa Nicholas Dibal; Danjuma S Yawas
Abstract
This study considered the consequence of the length and weight composition percentage of Deleb palm fruit fiber on the physio-mechanical characteristics of an epoxy-based composite through the Taguchi grey relational optimization technique. Considering fiber reinforcement of 30-40 wt% and fiber reinforcement ...
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This study considered the consequence of the length and weight composition percentage of Deleb palm fruit fiber on the physio-mechanical characteristics of an epoxy-based composite through the Taguchi grey relational optimization technique. Considering fiber reinforcement of 30-40 wt% and fiber reinforcement length of 1-5mm, the physical and mechanical properties were determined based on standards. The findings demonstrated that the Deleb palm fruit fiber's characteristics tend to differ from those of other types of fiber reinforcement in that they significantly impact the physio-mechanical characteristics of the resulting epoxy-based reinforced Deleb palm fruit fiber composite. The ANOVA result showed that, at a confidence interval of 5%, the effects of the fiber characteristics on the physio-mechanical properties of the composites were particularly notable for tensile strength and a decrease in water absorption.
Research Paper
Quality Control
Forbes Chiromo; Nomupendulo Nokuthula Msibi
Abstract
This single case study examined how key internal audit planning and implementation determinants impacted a South African automotive company's ISO 9001 Quality Management System objectives. The study used a mixed method approach; qualitative data nesting in quantitative data. The purposive sampling technique ...
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This single case study examined how key internal audit planning and implementation determinants impacted a South African automotive company's ISO 9001 Quality Management System objectives. The study used a mixed method approach; qualitative data nesting in quantitative data. The purposive sampling technique was used to collect primary data from managers, internal quality auditors, and auditees. Professional judgment was used to collect secondary data from the 2017 to 2020 audit reports. Descriptive data analysis was conducted on the data collected. The internal audits were conducted beyond departmental boundaries and organizational structures. The audit determinants were; compliance with the ISO 9001 standards, and maintenance of ISO 9001 QMS certification. The process and system internal quality audits were conducted to correct nonconformities before and after external audits. Audit reports from certification bodies also determined the scope of the subsequent internal audit programs for processes and systems. In addition, the internal auditors relied on their judgments and on the technical experts' advice to sample processes, areas, and material to be audited. Management audit review reports also contributed to determining the scope of audit programs. Despite different stakeholders' contributions, the company's internal quality audit programs did not embrace customer focus and continuous improvement. The audit program was a reaction to internal and external stakeholders' complaints. However, the study is fundamental to improving the company's ISO 9001 quality management system performance. It discusses issues that drive the planning and implementation of audit programs. The findings are likely to stimulate similar research in other sectors and on a bigger scale. There are also opportunities to evaluate the determinants related to monitoring, reviewing, and improving audit programs.
Research Paper
Game theory
Mohammad Shafiekhani; Alireza Rashidi Komijan; Hassan Javanshir
Abstract
The process of transferring money from the treasury to the branches and returning it at specific and limited periods is one of the applications of the Vehicle Routing Problem (VRP). Many parameters affect it but choosing the right route is the most key parameter so that the money delivery process is ...
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The process of transferring money from the treasury to the branches and returning it at specific and limited periods is one of the applications of the Vehicle Routing Problem (VRP). Many parameters affect it but choosing the right route is the most key parameter so that the money delivery process is carried out in a specific period with the least risk. In the present paper, new relationships are defined in the form of three concepts in order to minimize route risk. These concepts are: (i)the vehicle does not travel long routes in the first three movements. (ii)A branch is not served at the same hours on two consecutive days. (iii)An arc should not be repeated on two consecutive days. The proposed model with real information received from Bank Shahr has been performed for all branches in Tehran. Because the vehicle routing problem is an NP-Hard problem, a genetic algorithm was used to solve the problem. Different problems in various production dimensions were solved with GAMS and MATLAB software to show the algorithm solution quality. The results show that the difference between the genetic algorithm and the optimal solution is an average of 1.09% and a maximum of 1.75%.
Research Paper
Risk management
seyed reza seyed nezhad fahim; fatemeh Gholami gelsefid
Abstract
The primary purpose of this research was to understand the importance of supply chain strategies in the field of supply chain risk management, emphasizing the effectiveness and efficiency of agile and lean strategies to create resilience and robustness in the supply chain. Data was collected from 392 ...
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The primary purpose of this research was to understand the importance of supply chain strategies in the field of supply chain risk management, emphasizing the effectiveness and efficiency of agile and lean strategies to create resilience and robustness in the supply chain. Data was collected from 392 supply chain experts working in Iran's automotive industry to test hypotheses through structural equation modeling. The findings of this study show that market orientation (as an external force) has more signicant impact on the development of agile strategy than lean strategy. In contrast, the quality management system (as an internal force) is highly correlated with the development of lean supply chain strategies. Moreover, agile and lean strategies also have a signicant impact on a resilient and robust supply chain. The proposed model helps organizations understand and create an ideal supply chain by implementing the right combination of both agile and lean supply chain strategies, which in turn helps to create a resilient and robust supply chain. Therefore, the findings of this study help policymakers to improve supply chain strategies by incorporating new management practices. This is original research that has various valuable insights for academic researchers and also supply chain strategy professionals as it reveals empirical evidence of the past vital concepts.
Research Paper
Case studies in industry and services
Robert S Keyser; Parisa Pooyan
Abstract
In a Lean production environment, reduced setup times can lead to many benefits, including reduced lead times. Previous research has primarily relied on the SMED methodology and mathematical modeling to reduce setup times at machine centers – and both are very useful techniques. We use the Soft ...
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In a Lean production environment, reduced setup times can lead to many benefits, including reduced lead times. Previous research has primarily relied on the SMED methodology and mathematical modeling to reduce setup times at machine centers – and both are very useful techniques. We use the Soft Systems Methodology, combined with the Seven Tools of Quality, to provide a structured, illustrative means for diagnosing production and quality issues. A baseline average setup time was established by which future setup times would be compared. The intervention included brainstorming sessions between management and the converting center work crew that disclosed many reasons for increased setup times, some of which were under management’s control. Our findings resulted in a 24% reduction in average setup times and a 62% reduction in the moving range at a bottleneck machine center in the corrugated box industry.
Research Paper
Supply chain management
Javid Ghahremani-Nahr; Abdolsalaam Ghaderi; Ramez Kian
Abstract
This article deals with the modeling of the food bank (FB) network in the conditions of uncertainty in the demand of charities and the capacity of donating food. The importance of creating a FB network, along with providing quality food, led to consider the two objective functions of minimizing the costs ...
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This article deals with the modeling of the food bank (FB) network in the conditions of uncertainty in the demand of charities and the capacity of donating food. The importance of creating a FB network, along with providing quality food, led to consider the two objective functions of minimizing the costs of the total FB network and maximizing the minimum freshness of the food basket. The simultaneous optimization of the above two objective functions is aimed at making correct routing-inventory and allocation decisions. In this paper, food items in food baskets with high shelf-life and low shelf-life are considered. The results of solving the sample problems by combining the operators of two Genetic Algorithm (GA) and Salp Swarm Algorithm (SSA) showed that with the increase in the freshness of the food baskets, the costs of the FB network have increased. Also, the sensitivity analysis showed that the increase in uncertainty in the network leads to an increase in the cost of FB network and a decrease in the freshness of the food basket. The comparison of the results between the algorithms also showed that the efficiency of HGSSA is much higher than GA and SSA and the problem solving time by these methods is extremely lower. The use of HGSSA has increased the rate of achieving effective solutions by 14.06%.
Research Paper
Operations Research
hajar shirneshan; Ahmad Sadegheih; H. Hosseini-Nasab; mohammd mehdi lotfi
Abstract
Due to the importance of the health field, the problem of determining the shift scheduling of care providers has been addressed in many studies, and various methods have been proposed to solve it. Considering different skills and contracts for care providers is one of the essential issues in this field. ...
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Due to the importance of the health field, the problem of determining the shift scheduling of care providers has been addressed in many studies, and various methods have been proposed to solve it. Considering different skills and contracts for care providers is one of the essential issues in this field. Given the uncertainty in patients' demands, it is an important issue as to how to assign care providers to different shifts. One area facing this uncertainty is the provision of services to cancer patients. A stochastic programming model is developed to account for patient demand uncertainty by considering different skills and contracts for care providers in this study. In the first step, care providers are assigned to work shifts, then, in the second step, the required overtime hours are determined. The sample average approximation method is presented to determine an optimal schedule by minimizing care providers' regular and overtime costs with different contracts and skills. Then, the appropriate sample size is 100, which is determined based on the Monte Carlo and Latin Hypercube methods. In the following, the lower and upper bounds of the optimal solution are calculated. As the numerical results of the study show, the convergence of the lower and upper bounds of the optimal solution is obtained from the Latin Hypercube method. The best solution is equal to 189247.3 dollars and is achieved with a difference of 0.143% between the upper bound and lower bounds of the optimal solution. The Monte Carlo simulation method is used to validate the care provider program in the next stage. As shown, in the worst case, the value of the objective function is equal to 197480 dollars.
Research Paper
Engineering Computations
Ali Mahmoudloo
Abstract
We use the charge extraction by linearly increasing voltage (CELIV) technique to calculate the drift velocity and mobility of holes in organic semiconducting polymers . The essence of this technique to measure the charge carrier mobility is very simple. The charge carrier mobility is defined as carrier ...
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We use the charge extraction by linearly increasing voltage (CELIV) technique to calculate the drift velocity and mobility of holes in organic semiconducting polymers . The essence of this technique to measure the charge carrier mobility is very simple. The charge carrier mobility is defined as carrier drift velocity v in a given electric field E. It is a complimentary technique in the sense that it allows to study materials when other techniques such as Time-of-Flight are inapplicable. Typically, Photo-CELIV is used to measure the charge carrier mobility in organic semiconductors since they are large bandgap (2 eV or so) and not much thermally generated carriers are present for extraction in the dark. The effect of recombination mechanism on the carrier mobility in the organic layer is investigated.
Research Paper
Corporate Finance
Maryam Mohammad Ganji Nik; Gholamhosein Golarzi; Mohsen Shafiei Nikabadi; Mohammadjavad Fadaiei Eslam
Abstract
In this study, we explain the possible future scenarios of factors affecting stock price fluctuations in the Tehran Stock Exchange, with Respect to 2026 Perspective. This research is applied, cross-sectional, and qualitative, and is implemented as a descriptive survey using the scenario planning Approach. ...
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In this study, we explain the possible future scenarios of factors affecting stock price fluctuations in the Tehran Stock Exchange, with Respect to 2026 Perspective. This research is applied, cross-sectional, and qualitative, and is implemented as a descriptive survey using the scenario planning Approach. The statistical population is a collection of financial experts; We selected 15 of them as a sample using the judgmental/purposive and network (snowball) sampling methods. In the first step, we identified the key uncertainties of the factors affecting stock price fluctuations using the Fuzzy Delphi method, then by identifying the possible modes of each of the key uncertainties, three compatible scenarios were determined by Scenario Wizard software, and finally, the experts suggested strategies for these scenarios.
Research Paper
Data Envelopment Analysis, DEA
Shokouh Shahbeyk; Shokoofe Banihashemi
Abstract
One of the most important aspects of credit risk management is determining the capital requirement to cover the credit risk in a bank loan portfolio. This paper discusses the credit risk of a loan portfolio can be obtained by the stochastic recovery rate based on two approaches: beta distribution and ...
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One of the most important aspects of credit risk management is determining the capital requirement to cover the credit risk in a bank loan portfolio. This paper discusses the credit risk of a loan portfolio can be obtained by the stochastic recovery rate based on two approaches: beta distribution and short interest rates. The capital required to cover the credit risk is achieved through the Vasicek model. Also, the Black-Scholes Merton model for european call option is utilized to quantify the probability of default. Value-at-Risk (VaR) and Conditional Value-at-Risk (CVaR) are utilized as measures of risk to evaluate the level of risk obtained by the worst-case Probability Of Default (PD) a stochastic recovery rate is used for calculating VaR which relates to the underlying intensity default. In addition, the intensity default process is assumed to be linear in the short-term interest rate, which is driven by a CIR process. By considering the relevant characteristics with Data Envelopment Analysis (DEA) method, the loan portfolio performance is evaluated. This study proposes the losses which are driven by the stochastic recovery rate and default probability. The empirical investigation measures the PD of eighth stocks from different industries of the Iran stock exchange market by using the Black-Sholes-Merton model.
Research Paper
Performance evaluation and benchmarking
SUPRIYATI SUPRIYATI
Abstract
Company is an organization that provides or produces products/services. Various types of companies and the complexity of the process make the company must be able to continue to grow and compete with competitors. To win the competition, companies must have a strategy to improve performance. TPM is part ...
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Company is an organization that provides or produces products/services. Various types of companies and the complexity of the process make the company must be able to continue to grow and compete with competitors. To win the competition, companies must have a strategy to improve performance. TPM is part of the strategy implemented in the company. In Indonesia, not all companies apply TPM, automotive component painting companies apply and measure performance through PQCDSM as a whole. The result of TPM implementation is an increase in production performance which has an impact on reducing quality costs, increasing production, increasing the effectiveness of equipment use because the total of damaged equipment is less. TPM implementation through OEE production performance/engine efficiency increased by 68.7%
Research Paper
Forecasting, production planning, and control
Samrad Jafarian-Namin; Davood Shishebori; Alireza Goli
Abstract
The temperature has been a highly discussed issue in climate-changing. Predicting it plays an essential role in human affairs and lives. It is a challenging task to provide an accurate prediction of air temperature because of its complex and chaotic nature. This issue has drawn attention to utilizing ...
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The temperature has been a highly discussed issue in climate-changing. Predicting it plays an essential role in human affairs and lives. It is a challenging task to provide an accurate prediction of air temperature because of its complex and chaotic nature. This issue has drawn attention to utilizing the advances in modeling capabilities. ARIMA is a popular model for describing the underlying stochastic structure of available data. Artificial neural networks (ANNs) can also be appropriate alternatives. In the literature, forecasting the temperature of Tehran using both techniques has not been presented so far. Therefore, this article focuses on modeling air temperatures in the Tehran metropolis and then forecasting for twelve months by comparing ANN with ARIMA. Particle swarm optimization (PSO) can help deal with complex problems. However, its potential for improving the performance of forecasting methods has been neglected in the literature. Thus, improving the accuracy of ANN using PSO is investigated as well. After evaluations, applying the seasonal ARIMA model is recommended. Moreover, the improved ANN by PSO outperforms the pure ANN in predicting air temperature
Research Paper
Data Envelopment Analysis, DEA
Leila Khoshandam; Maryam Nematizadeh
Abstract
The inverse data envelopment analysis (DEA) problem has been one of the most important issues in the last decade. The inverse DEA permits the chief manager to increase (or decrease) outputs (or inputs) of decision-making units (DMUs) in such a way that the level of the relative efficiency of the under–observed ...
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The inverse data envelopment analysis (DEA) problem has been one of the most important issues in the last decade. The inverse DEA permits the chief manager to increase (or decrease) outputs (or inputs) of decision-making units (DMUs) in such a way that the level of the relative efficiency of the under–observed DMU is preserved. Due to the importance of network-structured production systems in real life, the main purpose of the present research is to provide an inverse DEA model for a two-stage network-structured production system in the presence of undesirable factors. The weak disposability assumption is used to handle undesirable outputs in the proposed model. The focus of the proposed model is on estimating the amount of change in one or more indicators of one stage of the process by changing the indicators of another stage to preserve the level of efficiency. The most important advantage of the proposed procedure is that it can increase the level of outputs and simultaneously reduce the level of inputs. To demonstrate its practical use, the model is applied to a real-life example in poultry farming.
