Allameh Tabataba'i UniversityIndustrial Management Studies2251-8029154420170321Analysis the enablers of flexible manufacturing system, using interpretive structural modelling and
Interpretive ranking processAnalysis the enablers of flexible manufacturing system, using interpretive structural modelling and
Interpretive ranking process126733610.22054/jims.2017.7336FAHamid RezaTalaieAkbarAlem TabrzHasanFarsijaniJournal Article20151006The volatile condition of today’s market is forcing the manufacturing managers to adapt the flexible manufacturing systems (FMS) to meet the challenges imposed by international competition, ever changing customer demands, rapid delivery to market and advancement in technology. Despite various barriers to implementation and development of FMS, there are enablers which facilitate this issue. One of the most important issues in this field and also the aim of this paper is to analysis the behavior of these enablers in order to effective utilization of them in the implementation and development of FMS. Enablers identified through literature review and industrial, and academic experts' opinion. Interpretive structural modelling (ISM) is used to develop a hierarchical structure for analyzing the interactions among enablers. Interpretive ranking process (IRP) is then used to examine the dominance relationship. ISM model highlights the importance of top management commitment and Financial investment over other enablers, whereas IRP model revealed supply chain management and operational and control techniques as the most important enablers due to performance areas. This study also gives a comparative account of ISM and IRP and shows that IRP is a more powerful tool, since it goes one-step further and considers the relationship of enablers with measurable performance indicatorsThe volatile condition of today’s market is forcing the manufacturing managers to adapt the flexible manufacturing systems (FMS) to meet the challenges imposed by international competition, ever changing customer demands, rapid delivery to market and advancement in technology. Despite various barriers to implementation and development of FMS, there are enablers which facilitate this issue. One of the most important issues in this field and also the aim of this paper is to analysis the behavior of these enablers in order to effective utilization of them in the implementation and development of FMS. Enablers identified through literature review and industrial, and academic experts' opinion. Interpretive structural modelling (ISM) is used to develop a hierarchical structure for analyzing the interactions among enablers. Interpretive ranking process (IRP) is then used to examine the dominance relationship. ISM model highlights the importance of top management commitment and Financial investment over other enablers, whereas IRP model revealed supply chain management and operational and control techniques as the most important enablers due to performance areas. This study also gives a comparative account of ISM and IRP and shows that IRP is a more powerful tool, since it goes one-step further and considers the relationship of enablers with measurable performance indicatorshttps://jims.atu.ac.ir/article_7336_ca733b212daf3851482883efa48bd4c9.pdfAllameh Tabataba'i UniversityIndustrial Management Studies2251-8029154420170321Designing Mathematical Model for Examinations Timetable in Universities and its Solutions AnalysisDesigning Mathematical Model for Examinations Timetable in Universities and its Solutions Analysis2750733710.22054/jims.2017.7337FAHosseinShams Shemirani1MahdiBashiriMohammadModarresJournal Article20150818In this research, optimization of examinations' timetable for university courses, based on a real problem in one of the universities in Iran is studied. The objective function defined for this problem is more practical and realistic than the other objective functions that have been utilized by previous researchers in literature and effectively reflects the real objective of the problem. In order to define the objective function, we have made use of Coulomb's law in electricity that says the magnitude of the electrostatic force of interaction between two point charges is directly proportional to the scalar multiplication of the magnitudes of the charges and inversely proportional to the square of the distance between them. We have defined a repulsive force between any pair of Examinations. The optimum solution is achieved when the sum of all forces is minimized. Hence, the obtained mathematical model is a non-linear programming with binary variables, similar to the quadratic assignment problem (QAP) which is an NP-Hard problem. This sort of problems can be solved exactly only if they are in small sizes. For solving this problem in medium and large scale, some methods are used based on Simulated Annealing (SA) algorithm and Imperialist Competitive algorithm (ICA). These algorithms can reach good sub-optimal solutions in a short period of time. Practical results of this mathematical model are already used in one of the national universities in Iran. The practical results demonstrate the high efficiency and effectiveness of this model.In this research, optimization of examinations' timetable for university courses, based on a real problem in one of the universities in Iran is studied. The objective function defined for this problem is more practical and realistic than the other objective functions that have been utilized by previous researchers in literature and effectively reflects the real objective of the problem. In order to define the objective function, we have made use of Coulomb's law in electricity that says the magnitude of the electrostatic force of interaction between two point charges is directly proportional to the scalar multiplication of the magnitudes of the charges and inversely proportional to the square of the distance between them. We have defined a repulsive force between any pair of Examinations. The optimum solution is achieved when the sum of all forces is minimized. Hence, the obtained mathematical model is a non-linear programming with binary variables, similar to the quadratic assignment problem (QAP) which is an NP-Hard problem. This sort of problems can be solved exactly only if they are in small sizes. For solving this problem in medium and large scale, some methods are used based on Simulated Annealing (SA) algorithm and Imperialist Competitive algorithm (ICA). These algorithms can reach good sub-optimal solutions in a short period of time. Practical results of this mathematical model are already used in one of the national universities in Iran. The practical results demonstrate the high efficiency and effectiveness of this model.https://jims.atu.ac.ir/article_7337_dcc8b6dced75d63c482b28b015d891a1.pdfAllameh Tabataba'i UniversityIndustrial Management Studies2251-8029154420170321Using Gray Relation Analysis and Entropy Methods in Ranking Corporates’ Social Responsibility: Evidence from Iranian Pharmaceutical CompaniesUsing Gray Relation Analysis and Entropy Methods in Ranking Corporates’ Social Responsibility: Evidence from Iranian Pharmaceutical Companies5174733810.22054/jims.2017.7338FANasserSanoubar0000-0002-7354-0222SaeidBazmohammadiJournal Article20150427Analyzing corporate social responsibility (CSR) is a multi-criteria problem. This paper firstly introduces gray relation and entropy weighting methods in order to find a solution to analyze and rank corporations from this point of view. The proposed technique that conducted through combining these two methods, will become more reliable decision making criterion. Furthermore, since in literature there are different dimensions suggested for CSR, entropy method is used to determine the relative importance of each dimension. Awareness-raising questionnaire prepared by the social responsibility unit of European Commission was used to measure corporate responsibility. By applying these methods, 10 active pharmaceutical material and products manufacturing corporations were investigated and in terms of paying attention to social responsibilities, Pars Daro corporation placed first. This technique not only helps corporations to diagnose their weaknesses and strengths, but also helps them to know their position against competitors and make better decisions to promote corporate rank in social responsibility.Analyzing corporate social responsibility (CSR) is a multi-criteria problem. This paper firstly introduces gray relation and entropy weighting methods in order to find a solution to analyze and rank corporations from this point of view. The proposed technique that conducted through combining these two methods, will become more reliable decision making criterion. Furthermore, since in literature there are different dimensions suggested for CSR, entropy method is used to determine the relative importance of each dimension. Awareness-raising questionnaire prepared by the social responsibility unit of European Commission was used to measure corporate responsibility. By applying these methods, 10 active pharmaceutical material and products manufacturing corporations were investigated and in terms of paying attention to social responsibilities, Pars Daro corporation placed first. This technique not only helps corporations to diagnose their weaknesses and strengths, but also helps them to know their position against competitors and make better decisions to promote corporate rank in social responsibility.https://jims.atu.ac.ir/article_7338_57b1f05c2cbdb0e5898445cc7a3f1a52.pdfAllameh Tabataba'i UniversityIndustrial Management Studies2251-8029154420170321The combination of Delphi method and Shannon entropy to deal with administrative corruption, using Fuzzy Inference SystemThe combination of Delphi method and Shannon entropy to deal with administrative corruption, using Fuzzy Inference System75116733910.22054/jims.2017.7339FAHamedRahmaniMortezaMoosakhaniGholamrezaMemarzade TehranKaramollahDaneshfardAbolfazlKazemiJournal Article20160103Referring to a variety of media and news headlines, we can figure out the increase in the phenomenon of corruption in the country. One of the applied mechanisms by international organizations like international transparency and global bank is applying Governance Model to combat against Corruption. There are different theories about good governance and the most controversial one is the mechanism of social control. In this theory, an appropriate model for governance in government systems is the combination of police power (force), exchange and persuasion in a variety of organizations. The aim of this study is to identify this combination in different organizations to combat against corruption. The present study is a developed research kind that has utilized Fuzzy Inference System for identification the mixture of three forces. For constructing fuzzy rules in the present study, we have applied mixed method of Shannon entropy and Delphi analysis. Shannon entropy has been used for analyzing the coefficients of the components of corruption in the organizations and as an "if" part of the rules, furthermore Delphi analysis has been applied for analysis of the combination of the social control or as a "then" part of the rules. The results of the study were applied as an " if and then" rules for analyzing six areas of a model. The three areas, related to Grand Corruption, included law enforcement agencies, financial and normative as well as three other areas related to Petty Corruption including law enforcement organizations, financial and normative. These procedures were applied in Fuzzy Inference System and the results have been analyzedReferring to a variety of media and news headlines, we can figure out the increase in the phenomenon of corruption in the country. One of the applied mechanisms by international organizations like international transparency and global bank is applying Governance Model to combat against Corruption. There are different theories about good governance and the most controversial one is the mechanism of social control. In this theory, an appropriate model for governance in government systems is the combination of police power (force), exchange and persuasion in a variety of organizations. The aim of this study is to identify this combination in different organizations to combat against corruption. The present study is a developed research kind that has utilized Fuzzy Inference System for identification the mixture of three forces. For constructing fuzzy rules in the present study, we have applied mixed method of Shannon entropy and Delphi analysis. Shannon entropy has been used for analyzing the coefficients of the components of corruption in the organizations and as an "if" part of the rules, furthermore Delphi analysis has been applied for analysis of the combination of the social control or as a "then" part of the rules. The results of the study were applied as an " if and then" rules for analyzing six areas of a model. The three areas, related to Grand Corruption, included law enforcement agencies, financial and normative as well as three other areas related to Petty Corruption including law enforcement organizations, financial and normative. These procedures were applied in Fuzzy Inference System and the results have been analyzedhttps://jims.atu.ac.ir/article_7339_36759d63600a08e47644cc1ec01a8880.pdfAllameh Tabataba'i UniversityIndustrial Management Studies2251-8029154420170321Evaluation of system and subsystem of Tehran’s subway trains ventilation using three-stage fuzzy relational data envelopment analysisEvaluation of system and subsystem of Tehran’s subway trains ventilation using three-stage fuzzy relational data envelopment analysis117157734010.22054/jims.2016.7340FASeyed AlirezaMir Mohammad Sadeghi*,MahdiMoghanMahdiKeshavarzMehrnooshKeshavarzFatemehKhaje NoriJournal Article20150829Subway network extension, growing expansion an inherent management complexities, made it necessary to use scientific approach, modern technology and global experiences about maintenance. Many equipments and trains of subway network, consist of repairable items which consume considerable human and financial resources of the organization. This paper aims to measure the efficiency and rank ventilation system of Tehran's DC trains and it's subsystems using three-stage relational data envelopment analysis model. About the importance of Tehran’s subway ventilation system, we can say that for 8 months of the year, ventilation system after driving engines which support the movement of trains, gets most important attention of operation management. In this paper with defining ventilation system as decision-making units, we use it to evaluate the system performance and ultimately for maintenance strategy, including an estimate of the maintenance workshop capacity, spare parts and requiring labor. Due to various errors such as human errors, machinery errors, limitations of field data analysis and etc, in this paper fuzzy logic is used to overcome the uncertainly in data. Also, reliability, availability and maintainability analysis, which are most important indicators in the maintenance field, have been used to determine the ventilation system inputs and outputsSubway network extension, growing expansion an inherent management complexities, made it necessary to use scientific approach, modern technology and global experiences about maintenance. Many equipments and trains of subway network, consist of repairable items which consume considerable human and financial resources of the organization. This paper aims to measure the efficiency and rank ventilation system of Tehran's DC trains and it's subsystems using three-stage relational data envelopment analysis model. About the importance of Tehran’s subway ventilation system, we can say that for 8 months of the year, ventilation system after driving engines which support the movement of trains, gets most important attention of operation management. In this paper with defining ventilation system as decision-making units, we use it to evaluate the system performance and ultimately for maintenance strategy, including an estimate of the maintenance workshop capacity, spare parts and requiring labor. Due to various errors such as human errors, machinery errors, limitations of field data analysis and etc, in this paper fuzzy logic is used to overcome the uncertainly in data. Also, reliability, availability and maintainability analysis, which are most important indicators in the maintenance field, have been used to determine the ventilation system inputs and outputshttps://jims.atu.ac.ir/article_7340_b653f2de54ef709dbbbf1249d05984b3.pdfAllameh Tabataba'i UniversityIndustrial Management Studies2251-8029154420170321Solving ATM Locating Problem Using Fuzzy Multi-Objective programmingSolving ATM Locating Problem Using Fuzzy Multi-Objective programming159185734110.22054/jims.2016.7341FAHamidShahbandarzadehMohammad HosseinKabganiJournal Article20151004This paper focused on locating ATMs problem. At first, this paper aims to identify effective factors in selecting ATMs appropriate locations. After selecting potential locations, optimal locations are determined through mathematical modeling. In this paper, effective factors to determine potential locations are weighted through Fuzzy AHP. Finally, linear allocation technique with multi-objective approach is used to determine ATMs locations at Bushehr city. After literature review, 46 effective factors are identified and then, based on experts' opinion are categorized in 6 groups of demographic, economic - social factors, competitive – commercial factors, public utility (infrastructure and proximity) factors, investment factors and political - legal factors. Results from Fuzzy AHP show that demographic factors are the most important factors among others. Final results show that each of these six categories, can have different effects on decision makers.This paper focused on locating ATMs problem. At first, this paper aims to identify effective factors in selecting ATMs appropriate locations. After selecting potential locations, optimal locations are determined through mathematical modeling. In this paper, effective factors to determine potential locations are weighted through Fuzzy AHP. Finally, linear allocation technique with multi-objective approach is used to determine ATMs locations at Bushehr city. After literature review, 46 effective factors are identified and then, based on experts' opinion are categorized in 6 groups of demographic, economic - social factors, competitive – commercial factors, public utility (infrastructure and proximity) factors, investment factors and political - legal factors. Results from Fuzzy AHP show that demographic factors are the most important factors among others. Final results show that each of these six categories, can have different effects on decision makers.https://jims.atu.ac.ir/article_7341_4db56dbbc012d7e37f34a526ef016f29.pdfAllameh Tabataba'i UniversityIndustrial Management Studies2251-8029154420170321A Multi-product model considering holding and purchasing Costs as an increasing function of order cycle timeA Multi-product model considering holding and purchasing Costs as an increasing function of order cycle time187208734210.22054/jims.2016.7342FAMahnazAfrasiyabiAhmadSadeghiJournal Article20141126In this paper classical inventory models, EOQ and EPQ, are developed considering holding and purchasing costs as an increasing continuous function of the ordering cycle time. Two models are presented: first one is economic order quantity and the second one is economic production quantity. Both models are formulated such that backorder is not permitted. Since the obtained model is a type of nonlinear continuous program, solving it with exact methods is impossible at the reasonable time, hence genetic algorithm and particle swarm optimization algorithm are presented to solve the problems. In addition, to increase effectiveness of algorithms, Taguchi method is used for parameters tuning. Finally a numerical example is presented to comprise two methods and results are illustrated.In this paper classical inventory models, EOQ and EPQ, are developed considering holding and purchasing costs as an increasing continuous function of the ordering cycle time. Two models are presented: first one is economic order quantity and the second one is economic production quantity. Both models are formulated such that backorder is not permitted. Since the obtained model is a type of nonlinear continuous program, solving it with exact methods is impossible at the reasonable time, hence genetic algorithm and particle swarm optimization algorithm are presented to solve the problems. In addition, to increase effectiveness of algorithms, Taguchi method is used for parameters tuning. Finally a numerical example is presented to comprise two methods and results are illustrated.https://jims.atu.ac.ir/article_7342_e0f4fbb49b8b7ff457f749fe7b605e2c.pdf