Shahid Beheshti UniversityJournal of Industrial Management Perspective2251-98743420140220Interpretive Structural Modeling for Project Supply Chain Risks in State Gas CompanyInterpretive Structural Modeling for Project Supply Chain Risks in State Gas Company93787297FAAliMohammadiProfessor, Shiraz University.AlinaghiMosleh ShiraziAssociate Professor, Shiraz University, Shiraz.Mohammad BagherAhmadiAssociate Professor, Shiraz University.PayamShojaeiPh.D. Student, Shiraz University.Journal Article20190927This article is aimed at identifying effective risks on gas projects supply chain in State gas companies. To achieve this aim, firstly, according to the literature we have identified risk categories by using meta-synthesis and then we have found the risks which are related to gas projects through applying content validity. Then, the relationship between risks is determined by ISM and their motivating power and dependency were clarified. Proposed method indicated that political/social and macroeconomic risks from outside of gas industry have the most effect on gas industry function. This model helps the managers to have a systematic view of risks in industry and also they can follow the political/social changes and fluctuations of macroeconomic condition in order to reduce negative effects.This article is aimed at identifying effective risks on gas projects supply chain in State gas companies. To achieve this aim, firstly, according to the literature we have identified risk categories by using meta-synthesis and then we have found the risks which are related to gas projects through applying content validity. Then, the relationship between risks is determined by ISM and their motivating power and dependency were clarified. Proposed method indicated that political/social and macroeconomic risks from outside of gas industry have the most effect on gas industry function. This model helps the managers to have a systematic view of risks in industry and also they can follow the political/social changes and fluctuations of macroeconomic condition in order to reduce negative effects.https://jimp.sbu.ac.ir/article_87297_278bda2adf6abb178edb87d77a78a1b9.pdfShahid Beheshti UniversityJournal of Industrial Management Perspective2251-98743420140220Implementation of Neural Networks in Group Technology and Its Comparison to the Results of K-means, Similarity Coefficient Method and Rank Order ClusteringImplementation of Neural Networks in Group Technology and Its Comparison to the Results of K-means, Similarity Coefficient Method and Rank Order Clustering396287298FAAli RezaPooyaAssociate professor, Ferdowsi University of Mashhad.0000-0001-6000-3535EhsanJavan RadPhD. Student, Ferdosi University.Journal Article20190927The most important problem during implementation of group technology in industrial units is firstly, part family formation and grouping parts according to it and secondly, achieving consistency during the time. There are different methods for grouping of parts. When we use part attributes for grouping. The first and the most important stage is designing of a part coding system and identification of parts on the basis of it. This paper investigated application of a back propagation neural network in part grouping for connectors pins and their attributes.And its results were compared to grouping results of K-means cluster analysis, similarity coefficient method and ROC method. Finally the results showed the capability of neural networks for parts grouping on the basis of their attributes and preference of neural networks to K-meanscluster analysis.The most important problem during implementation of group technology in industrial units is firstly, part family formation and grouping parts according to it and secondly, achieving consistency during the time. There are different methods for grouping of parts. When we use part attributes for grouping. The first and the most important stage is designing of a part coding system and identification of parts on the basis of it. This paper investigated application of a back propagation neural network in part grouping for connectors pins and their attributes.And its results were compared to grouping results of K-means cluster analysis, similarity coefficient method and ROC method. Finally the results showed the capability of neural networks for parts grouping on the basis of their attributes and preference of neural networks to K-meanscluster analysis.https://jimp.sbu.ac.ir/article_87298_6dce8475195975854ff7734027f90088.pdfShahid Beheshti UniversityJournal of Industrial Management Perspective2251-98743420140220Integrating Sustainability into Supplier Selection and Order Quantity AllocationIntegrating Sustainability into Supplier Selection and Order Quantity Allocation638587299FAKamalChaharsoghiProfessor, Tarbiat modares University.MehdiAshrafiPh.D. Student, Tarbiat Modares University.Journal Article20190927Supplier selection is an important decision in the management of a supply chain. Recent emphasis on sustainability in supply chain management has made this selection more complex. In this paper the sustainable supplier selection criteria and sub-criteria are determined. Based on those criteria and sub-criteria a methodology is proposed in supplier evaluation and order allocation. Gray relational analysis is used to sustainability supplier evaluation and a bilinear goal programming model is developed for supplier selection and order allocation. Bilinearity in the model is handled with a modified Benders decomposition method and numerical results shows the efficiency of the proposed model. Implications of the model and future research directions are presented as the paper conclusion.Supplier selection is an important decision in the management of a supply chain. Recent emphasis on sustainability in supply chain management has made this selection more complex. In this paper the sustainable supplier selection criteria and sub-criteria are determined. Based on those criteria and sub-criteria a methodology is proposed in supplier evaluation and order allocation. Gray relational analysis is used to sustainability supplier evaluation and a bilinear goal programming model is developed for supplier selection and order allocation. Bilinearity in the model is handled with a modified Benders decomposition method and numerical results shows the efficiency of the proposed model. Implications of the model and future research directions are presented as the paper conclusion.https://jimp.sbu.ac.ir/article_87299_93e82c989ac2f16740953e3e5b3c3152.pdfShahid Beheshti UniversityJournal of Industrial Management Perspective2251-98743420140220Presentation an Agile Organization Performance Measurement Model: an Interpretive Structural Modeling ApproachPresentation an Agile Organization Performance Measurement Model: an Interpretive Structural Modeling Approach8710987300FARohollahRaziniAssistant Professor, Imam Sadeq University.AdelAzarProfessor, Tarbiat Modares University.0000-0003-2123-7579MahdiMohammadiPh.D Student, Mazandaran University.Journal Article20190927Nowadaysorganizationshavechosen a new approachnamedagility to respond thechallenges ofthe business environment. The requirements of this approach have affected on how to measure the performance of these organizations. Inrecent years, the contingencymodel ofperformance measurementhasattractedthe attention of manyscholars to response theturbulentenvironment.Itseems tofit the caseofdomesticenvironmentalorganizations. Optimum performancemeasurement modelof agileorganizationsshould bebuilt. This research uses literature reviewandextracts the performance measures from common and famousperformance measurementmodels.It measures affectingperformance measurementon agileorganizations. At first stage, the research classifiescriteriausingcognitivemappingmethodology. Then, it uses interpretive structural modeling for creating a model for performance measurement system of agile organizations. The results of the survey are derived in a model consists of 11 criteria and 8 level.Theseresults indicatetheimportance ofsuchcriteria asleadership,strategic planningand organizational culture as themost influentialparametersin theperformanceofagileorganizationsthathavean impacton otherfactors ofmodel.Nowadaysorganizationshavechosen a new approachnamedagility to respond thechallenges ofthe business environment. The requirements of this approach have affected on how to measure the performance of these organizations. Inrecent years, the contingencymodel ofperformance measurementhasattractedthe attention of manyscholars to response theturbulentenvironment.Itseems tofit the caseofdomesticenvironmentalorganizations. Optimum performancemeasurement modelof agileorganizationsshould bebuilt. This research uses literature reviewandextracts the performance measures from common and famousperformance measurementmodels.It measures affectingperformance measurementon agileorganizations. At first stage, the research classifiescriteriausingcognitivemappingmethodology. Then, it uses interpretive structural modeling for creating a model for performance measurement system of agile organizations. The results of the survey are derived in a model consists of 11 criteria and 8 level.Theseresults indicatetheimportance ofsuchcriteria asleadership,strategic planningand organizational culture as themost influentialparametersin theperformanceofagileorganizationsthathavean impacton otherfactors ofmodel.https://jimp.sbu.ac.ir/article_87300_53b8b63435c108101647ed5ec067cab7.pdfShahid Beheshti UniversityJournal of Industrial Management Perspective2251-98743420140220Development and Application of LINMAP, PROMETHEEIV, and FIS in Continuous Multi-Criteria Decision-Making ProblemsDevelopment and Application of LINMAP, PROMETHEEIV, and FIS in Continuous Multi-Criteria Decision-Making Problems11113687301FAMajidEsmaelianAssistant Professor, Isfahan University.SomayeMohammadyMA, University of Isfahan.Sayedeh MaryamAbdollahiMA, University of Isfahan.MoslemAlimohammadiMA, University of Isfahan.Journal Article20190927MCDM problems can be classified into multi-attribute decision making and multi-objective decision-making. In MADM methods, the decision space is discrete and there are a limited predetermined alternative, and preferred alternative has a total performance better than other alternatives in all criteria. Until now different version of out-ranking methods are used for decision making in discrete space while evaluated and ranked some predetermined options using several constant criteria. In most of multi-criteria decision problems, set of alternatives is not discrete and considered as a continuous sets. In this paper, PROMETHEE-IV, FIS and LINMAP techniques has been used for multi-criteria decision problems with continuous alternatives. Then we have been investigate a problem of continuous multi-criteria decision making, with four criteria and alternatives in continuous space to evaluate the performance of the proposed method. The results of numerical examples show the capability of the proposed model in finding the preferred point(s).MCDM problems can be classified into multi-attribute decision making and multi-objective decision-making. In MADM methods, the decision space is discrete and there are a limited predetermined alternative, and preferred alternative has a total performance better than other alternatives in all criteria. Until now different version of out-ranking methods are used for decision making in discrete space while evaluated and ranked some predetermined options using several constant criteria. In most of multi-criteria decision problems, set of alternatives is not discrete and considered as a continuous sets. In this paper, PROMETHEE-IV, FIS and LINMAP techniques has been used for multi-criteria decision problems with continuous alternatives. Then we have been investigate a problem of continuous multi-criteria decision making, with four criteria and alternatives in continuous space to evaluate the performance of the proposed method. The results of numerical examples show the capability of the proposed model in finding the preferred point(s).https://jimp.sbu.ac.ir/article_87301_6714fa9dfc460f115aaa584a1feecb31.pdfShahid Beheshti UniversityJournal of Industrial Management Perspective2251-98743420140220Emergency Department Simulation and Ranking Its Improving Scenarios using AHP – PROMETHEE MethodEmergency Department Simulation and Ranking Its Improving Scenarios using AHP – PROMETHEE Method13716487302FAMostafaKazemiAssociate Professor, Ferdowsi University of Mashhad.0000-0002-5084-5752AliSibeveihMA, Ferdosi Mashhad University.MohammadRanjbarAssociate Professor, Ferdosi Mashhad University.ZahraNaji AzimiAssociate professor, Ferdowsi University of Mashhad.RaziehKarimiNurse Expert, Ghaem Hospital, Mashhad.Journal Article20190927Due to the increasing health care organizations costs, their requirement to increase the quality, and also the complexity of their systems, the issue of the change and improvement to the systems has got really important. It was crucial to know which of methods and scenarios for the change of the systems, especially in the resources, lead to better conditions and this topic caused major issues. In this regard, discrete – event simulation as one of the decision making tools in operations research based on random data, has significantly helped policy makers and a managers. In this study, firstly, the key performance measures of Ghaem hospital emergency system using past publications and experts’ suggestions were identified. Then this system was modeled and simulated using Arena software. After weighting the criteria by AHP method, the scenarios of the experts were defined<span lang="FA" dir="RTL">. </span> Finally they were ranked using PROMETHEE method and the most suitable scenario was determined.Due to the increasing health care organizations costs, their requirement to increase the quality, and also the complexity of their systems, the issue of the change and improvement to the systems has got really important. It was crucial to know which of methods and scenarios for the change of the systems, especially in the resources, lead to better conditions and this topic caused major issues. In this regard, discrete – event simulation as one of the decision making tools in operations research based on random data, has significantly helped policy makers and a managers. In this study, firstly, the key performance measures of Ghaem hospital emergency system using past publications and experts’ suggestions were identified. Then this system was modeled and simulated using Arena software. After weighting the criteria by AHP method, the scenarios of the experts were defined<span lang="FA" dir="RTL">. </span> Finally they were ranked using PROMETHEE method and the most suitable scenario was determined.https://jimp.sbu.ac.ir/article_87302_8493d25b9932bc97b2c8c9cd06ee150d.pdfShahid Beheshti UniversityJournal of Industrial Management Perspective2251-98743420140220Group Decision Making using a Fuzzy Approach for Evaluating the Supply Chain Flexibility of Yazdbaf FactoryGroup Decision Making using a Fuzzy Approach for Evaluating the Supply Chain Flexibility of Yazdbaf Factory16518787303FAAlirezaNaser SadrabadyAssistant Professor, Yazd University.Seyed HabibollahMirghaforiAssociate Professor, Yazd University.Saide SadatSalariM.Sc., Science and Arts University.Journal Article20190927Due to changes in production and market conditions, companies are facing a lot of pressures. One way of dealing with these pressures is the concept of supply chain and its flexibility to satisfy different customers’ neeeds. Before any decision-making on supply chain flexibility, it is necessary to measure flexibility. In this study, using a fuzzy method based on modified linguistic ordered weighted geometric averaging operator in interactive group decision-making, of supply chain flexibility has been measured. In this measurement, sourcing flexibility, operating system flexibility, distribution flexibility and information system flexibility, are considered as the dimensions of supply chain flexibility. Case study research was conducted in Yazdbaf factory. Desired state and the current state Survey of this factory, shows that the factory supply chain needs to find the best way to improve supply chain flexibility of this factory. The paper concluded that the bestb way is to improve its information systems dimension. These results were accepted by the members of the group.Due to changes in production and market conditions, companies are facing a lot of pressures. One way of dealing with these pressures is the concept of supply chain and its flexibility to satisfy different customers’ neeeds. Before any decision-making on supply chain flexibility, it is necessary to measure flexibility. In this study, using a fuzzy method based on modified linguistic ordered weighted geometric averaging operator in interactive group decision-making, of supply chain flexibility has been measured. In this measurement, sourcing flexibility, operating system flexibility, distribution flexibility and information system flexibility, are considered as the dimensions of supply chain flexibility. Case study research was conducted in Yazdbaf factory. Desired state and the current state Survey of this factory, shows that the factory supply chain needs to find the best way to improve supply chain flexibility of this factory. The paper concluded that the bestb way is to improve its information systems dimension. These results were accepted by the members of the group.https://jimp.sbu.ac.ir/article_87303_cea69ffef58c6097b4d35f0e3d80ebbb.pdf