University of TehranIndustrial Management Journal2008-58857320150923A Model for Relationship of Supply Chain Risks in Iran’s Petrochemical IndustryA Model for Relationship of Supply Chain Risks in Iran’s Petrochemical Industry4054245725710.22059/imj.2015.57257FAAliAtashsoozPh.D. student, Faculty of Management and Accounting, Allameh Tabataba’i University, Tehran, Iran0000-0002-6014-7130KamranFeiziProfessor, Faculty of Management and Accounting, Allameh Tabataba’i University, Tehran, Iran.AbolfazlKazaziAssociate Prof., Faculty of Management and Accounting, Allameh Tabataba’i University, Tehran, Iran.LayaOlfatAssociate Prof., Faculty of Management and Accounting, Allameh Tabataba’i University, Tehran, Iran.0000-0003-4550-8775Journal Article20150524In a complex and volatile environment of the supply chain, any attempt to reduce the risks may increase or decrease other risks; thus, achieving an overall picture of the risks of supply chain and relationships between them are necessary and will lead to more effective and comprehensive strategy to response to risks. The purpose of this paper is identifying and extracting the potential risks of supply chain relationships using interpretive structural modeling (ISM) approach. In order to do that, first an in-depth literature review has done and experts opinions with content validity has used, and then, the ISM model representing the structure of risks relationship has extract and the final model has statistically tested using path analysis. The results show that the external environment supply chain risks (natural risks, political/social, policy and macroeconomic), at a low levels of the model, have the most driving power and organizational risks (operational, financial, strategic, liability and organizational culture and employee), at the top the model, are the most dependent risks. industrial risks (market and product competition; market inputs, communications and collaboration).In a complex and volatile environment of the supply chain, any attempt to reduce the risks may increase or decrease other risks; thus, achieving an overall picture of the risks of supply chain and relationships between them are necessary and will lead to more effective and comprehensive strategy to response to risks. The purpose of this paper is identifying and extracting the potential risks of supply chain relationships using interpretive structural modeling (ISM) approach. In order to do that, first an in-depth literature review has done and experts opinions with content validity has used, and then, the ISM model representing the structure of risks relationship has extract and the final model has statistically tested using path analysis. The results show that the external environment supply chain risks (natural risks, political/social, policy and macroeconomic), at a low levels of the model, have the most driving power and organizational risks (operational, financial, strategic, liability and organizational culture and employee), at the top the model, are the most dependent risks. industrial risks (market and product competition; market inputs, communications and collaboration).https://imj.ut.ac.ir/article_57257_04bd110323290a61088e9c75900211c4.pdfUniversity of TehranIndustrial Management Journal2008-58857320150923Designing a Model for Evaluation and Prioritizing of Contractors by Using Fuzzy analytic Hierarchy and Taguchi Loss FunctionDesigning a Model for Evaluation and Prioritizing of Contractors by Using Fuzzy analytic Hierarchy and Taguchi Loss Function4254445725810.22059/imj.2015.57258FAAbolghasemEbrahimiAssistant Professor of management Department , Shiraz University,shiraz,Iran0000-0002-6410-8809MoslemAlimohammadlouAssistant Professor of management Department , Shiraz University,shiraz,IranSaharMohammadiMSc. Student of industrial management, Shiraz University,shiraz,IranJournal Article20150429This Paper has been done with the goal of assessment and prioritization of contractors of Fars Province Electricity Distribution Company. Such decision makings are generally complicated and are essentially considered as an multi-criteria decision making process. If the tasks assigned to contractors are not performed appropriately, it would lead to loss. In other words, contractors who cause the least loss, are considered as those with the best performance. Taguchi’s loss function can be used in order to calculate the loss caused be contractors performance. In this paper, a model has been proposed using Fuzzy AHP and combining it with Taguchi’s loss function, in order to assess and rank the contractors. A great ranking of contractors based on their performance is obtained using this methodology. The input data of this model is acquired of twenty contractors of Fars Province Electricity Distribution Company in twenty-four criteria and the output of this model is the final points of cooperating with each contractor. The results show that the strongest and weakest contractor impose Loss of 29.20 and 98.15 percent, respectively, on company.This Paper has been done with the goal of assessment and prioritization of contractors of Fars Province Electricity Distribution Company. Such decision makings are generally complicated and are essentially considered as an multi-criteria decision making process. If the tasks assigned to contractors are not performed appropriately, it would lead to loss. In other words, contractors who cause the least loss, are considered as those with the best performance. Taguchi’s loss function can be used in order to calculate the loss caused be contractors performance. In this paper, a model has been proposed using Fuzzy AHP and combining it with Taguchi’s loss function, in order to assess and rank the contractors. A great ranking of contractors based on their performance is obtained using this methodology. The input data of this model is acquired of twenty contractors of Fars Province Electricity Distribution Company in twenty-four criteria and the output of this model is the final points of cooperating with each contractor. The results show that the strongest and weakest contractor impose Loss of 29.20 and 98.15 percent, respectively, on company.https://imj.ut.ac.ir/article_57258_a5e9386548ffc0bc48926a758249f91f.pdfUniversity of TehranIndustrial Management Journal2008-58857320150923Bi-objective Scheduling of no wait flexible flow lines with a time window and the possibility of work rejectingBi-objective Scheduling of no wait flexible flow lines with a time window and the possibility of work rejecting4454685725910.22059/imj.2015.57259FABabakAslaniMSc./ُShahid Beheshti UniversityMostafaZandiehAssociate Prof. Faculty of Management and ccounting /Shahid Beheshti University0000-0003-1209-9514MajidAdeliُShahid Beheshti University /ph.D studentJournal Article20150403One of the main challenges for manufacturers in production systems on order is balancing between orders, inputs and limited resources. Hence, they have to choose some orders and reject the others. In addition, work schedule must be considered in order acceptance. In this research the integrated problem of scheduling and order acceptance in a no wait flexible flow line production system is discussed. In this study orders that can’t be delivered in due date are rejected . Most researches are single objective optimization but in real world different objectives should be considered in the decision making. Therefor a bi-objective model which maximizes profit and minimize delivery deviation, is presented. Due to the high complexity of the model, the exact methods are not able to produce the optimal solution , so the two meta- heuristic algorithms MOSA and NSGA II for this problem were developed and their performance were compared through quantitative indicators in three different categories.One of the main challenges for manufacturers in production systems on order is balancing between orders, inputs and limited resources. Hence, they have to choose some orders and reject the others. In addition, work schedule must be considered in order acceptance. In this research the integrated problem of scheduling and order acceptance in a no wait flexible flow line production system is discussed. In this study orders that can’t be delivered in due date are rejected . Most researches are single objective optimization but in real world different objectives should be considered in the decision making. Therefor a bi-objective model which maximizes profit and minimize delivery deviation, is presented. Due to the high complexity of the model, the exact methods are not able to produce the optimal solution , so the two meta- heuristic algorithms MOSA and NSGA II for this problem were developed and their performance were compared through quantitative indicators in three different categories.https://imj.ut.ac.ir/article_57259_f1d728911606c0db577e8e9083e038c6.pdfUniversity of TehranIndustrial Management Journal2008-58857320150923A multi- objective project portfolio selection and scheduling problem under uncertainty (case study: company of Payafanavaran Ferdowsi)A multi- objective project portfolio selection and scheduling problem under uncertainty (case study: company of Payafanavaran Ferdowsi)4694885726010.22059/imj.2015.57260FAEbrahimRezaee NikAssistant Prof., Faculty of Industrial Engineering, Sadjad University of Technology, Mashhad, IranFaribaMolaviMSc. Student, Industrial Engineering, Sadjad University of Technology, Mashhad, IranJournal Article20141208Nowadays organization especially R&D centers are dealing with project portfolio selection decisions under uncertainty. Moreover in the most of the past research, project portfolio selection and scheduling are often considered to be independent problem. This leads to insufficient result in real world. So in this research simultaneous project portfolio selection and scheduling problem is modeling whose objectives are maximizing expected profit and minimizing risk. Moreover there is autocorrelation among annual earnings. Therefore an efficient time series methodology is used for forecasting. Another advantage of proposed model is considering uncertainty of project success and earnings and also risk of dealing with budget deficiency. Due to the complexity of problem, especially for large size, practical swarm, simulated annealing and genetic algorithm are presented and their efficiency is compared by a hypothetical example. The results show efficiency of simulated annealing algorithm in terms of quality and execution time. Finally the model is validated via its application to a knowledge based company in Ferdowsi University of Mashhad.Nowadays organization especially R&D centers are dealing with project portfolio selection decisions under uncertainty. Moreover in the most of the past research, project portfolio selection and scheduling are often considered to be independent problem. This leads to insufficient result in real world. So in this research simultaneous project portfolio selection and scheduling problem is modeling whose objectives are maximizing expected profit and minimizing risk. Moreover there is autocorrelation among annual earnings. Therefore an efficient time series methodology is used for forecasting. Another advantage of proposed model is considering uncertainty of project success and earnings and also risk of dealing with budget deficiency. Due to the complexity of problem, especially for large size, practical swarm, simulated annealing and genetic algorithm are presented and their efficiency is compared by a hypothetical example. The results show efficiency of simulated annealing algorithm in terms of quality and execution time. Finally the model is validated via its application to a knowledge based company in Ferdowsi University of Mashhad.https://imj.ut.ac.ir/article_57260_e08e1179b27de8e4dfbb60b9c15ee761.pdfUniversity of TehranIndustrial Management Journal2008-58857320150923Designing a Multi-objective Stochastic programming model for portfolio selectionDesigning a Multi-objective Stochastic programming model for portfolio selection4895105726110.22059/imj.2015.57261FAAlirezaSharifisalimPh.D. Student in Operational Research Management, Faculty of Management, Tehran University, , Tehran, Iran.MansourMomeniProf., Industrial Management, Faculty of Management, Tehran University, Tehran, Iran.0000-0002-9157-5584MohammadModarres YazdiProf., Industrial Engineering, Sharif University of Technology, Tehran, Iran.RezaRayiProf., Financial Management, Faculty of Management, Tehran University, Tehran, Iran.Journal Article20141119In traditional portfolio selection model coefficients often are certain and deterministic, but in real world these coefficients are probabilistic. So decision maker cannot estimate them exactly. Financial optimization is one of the most attractive areas in decision under uncertainty. In the portfolio selection problem the Decision Maker considers simultaneously conflicting objectives such as rate of return, liquidity, Dividend and risk. Multi-objective programming techniques such as goal programming and compromise programming are used to choose the portfolio best satisfying the Decision Maker’s aspirations and preferences; additionally Multi Criteria Decision Making (MCDM)Techniques for dealing with portfolio selection have been used. In this article, we assume that the parameters associated with the objectives are random and normally distributed. We propose a chance constrained compromise programming model is based on compromise programming and chance constrained programming models as a deterministic transformation to multi-objective stochastic programming portfolio model. To determine the share of industry investment planning MCDM were used. The result of the planning model for portfolio selection in Tehran Stock Exchange is shown.In traditional portfolio selection model coefficients often are certain and deterministic, but in real world these coefficients are probabilistic. So decision maker cannot estimate them exactly. Financial optimization is one of the most attractive areas in decision under uncertainty. In the portfolio selection problem the Decision Maker considers simultaneously conflicting objectives such as rate of return, liquidity, Dividend and risk. Multi-objective programming techniques such as goal programming and compromise programming are used to choose the portfolio best satisfying the Decision Maker’s aspirations and preferences; additionally Multi Criteria Decision Making (MCDM)Techniques for dealing with portfolio selection have been used. In this article, we assume that the parameters associated with the objectives are random and normally distributed. We propose a chance constrained compromise programming model is based on compromise programming and chance constrained programming models as a deterministic transformation to multi-objective stochastic programming portfolio model. To determine the share of industry investment planning MCDM were used. The result of the planning model for portfolio selection in Tehran Stock Exchange is shown.https://imj.ut.ac.ir/article_57261_4fefd0fa42c177883bca3943ad56ec9c.pdfUniversity of TehranIndustrial Management Journal2008-58857320150923project portfolio optimization considering project interactions using teaching-learning optimization alghorithmproject portfolio optimization considering project interactions using teaching-learning optimization alghorithm5115325726210.22059/imj.2015.57262FARezaSheikhAssistant Prof., Faculty of Industrial Engineering and Management, Shahrood University, Shahrood, IranMaryamAzariMSc,MBA, Shahrood University, Shahrood, IranJournal Article20140413: Nowadays, organizations are faced with a multitude of project and investment opportunities. Despite the importance of various criteria, complexity of multi-objective models and weakness of optimization algorithms often compelled manager to limit the selection criteria or only suffice to financial objects. In this paper, it is endeavored to extend selection criteria by using an efficient optimization algorithm based on teaching-learning process, which makes it possible to solve the proposed 0-1 multi-objective programing model. Finally efficiency of the applied algorithm called TLBO is compared with PSO and GA by applying the proposed model in a project oriented organization. It was shown that TLBO is better than GA and PSO algorithm technique, which was used before in such problems.: Nowadays, organizations are faced with a multitude of project and investment opportunities. Despite the importance of various criteria, complexity of multi-objective models and weakness of optimization algorithms often compelled manager to limit the selection criteria or only suffice to financial objects. In this paper, it is endeavored to extend selection criteria by using an efficient optimization algorithm based on teaching-learning process, which makes it possible to solve the proposed 0-1 multi-objective programing model. Finally efficiency of the applied algorithm called TLBO is compared with PSO and GA by applying the proposed model in a project oriented organization. It was shown that TLBO is better than GA and PSO algorithm technique, which was used before in such problems.https://imj.ut.ac.ir/article_57262_5c8377916321f5419f22a56765ae0a1c.pdfUniversity of TehranIndustrial Management Journal2008-58857320150923Measuring sustainability of service supply chain by using a multi-stage/multicast fuzzy inference system (Studied Case: Parsian BankMeasuring sustainability of service supply chain by using a multi-stage/multicast fuzzy inference system (Studied Case: Parsian Bank5335625726310.22059/imj.2015.57263FAMohamadrezaSadeghi MoghadamAssistant Prof., Faculty of Management, Tehran University, Tehran, Iran0000-0002-9584-5811HosseinSafariAssociate Prof., Faculty of Management, Tehran University, Tehran, Iran0000-0001-9232-1319MojtabaAhmadi NozariMSc. Student in Industrial Management, Faculty of Management, Tehran University, Tehran, IranJournal Article20150411Sustainable development tried to continuous development, beyond the economic development. Given the fundamental importance of banks in the economy and the importance of sustainability in recent years, this study aimed to measure sustainability of Parsian Bank and in general, the Iran's banking industry. The initial framework resulting from the review of the literature, sustainability reports of selected banks in the world and other reports in the area of sustainability with holding focus group sessions with industry experts is confirmed. In order to measure sustainability a multi-stage/multicast Fuzzy Inference System(FIS) was designed that able to measure sustainability in each of the 4 main structures identified, i.e. the social, environmental, economic and governance structures. Based on the output of this 4 structures, a FIS for measuring the specific form of the concept of sustainability in Parsian Bank planned that the output is number 0/798. For the final evaluation of the overall sustainability, the designed range in the Global Initiative Report was used. Due to the resulting number noted range, Parsian Bank has the A-level of sustainability.Sustainable development tried to continuous development, beyond the economic development. Given the fundamental importance of banks in the economy and the importance of sustainability in recent years, this study aimed to measure sustainability of Parsian Bank and in general, the Iran's banking industry. The initial framework resulting from the review of the literature, sustainability reports of selected banks in the world and other reports in the area of sustainability with holding focus group sessions with industry experts is confirmed. In order to measure sustainability a multi-stage/multicast Fuzzy Inference System(FIS) was designed that able to measure sustainability in each of the 4 main structures identified, i.e. the social, environmental, economic and governance structures. Based on the output of this 4 structures, a FIS for measuring the specific form of the concept of sustainability in Parsian Bank planned that the output is number 0/798. For the final evaluation of the overall sustainability, the designed range in the Global Initiative Report was used. Due to the resulting number noted range, Parsian Bank has the A-level of sustainability.https://imj.ut.ac.ir/article_57263_75ee5526e1d450006dbbad5158a5383f.pdfUniversity of TehranIndustrial Management Journal2008-58857320150923Energy resources optimal allocation in Iran regarding subsidies liftingEnergy resources optimal allocation in Iran regarding subsidies lifting5635865726410.22059/imj.2015.57264FAAliyehKazemiAssistant Prof. in Industrial Management, University of Tehran, Tehran, Iran0000-0002-0755-7800Mohammad RezaMehreganProf. in Industrial Management, University of Tehran, Tehran, IranHamedShakouri GanjaviAssociate Prof. in Industrial Engineering, University of Tehran, Tehran, Iran0000-0002-4293-1507Journal Article20150317This research presents a mathematical model for oil and gas optimal allocation to different sectors in Iran using operations research techniques. Sectors are residential and commercial, transportation, industries, agriculture, exports, injection to oil reservoirs and power plans as a secondary energy producer. Optimal allocation of energy resources to end-uses from 2011 to 2021 has been done using a linear programming model regarding lifting of subsidies. The results provide scientific basic for the optimal allocation of energy resources in Iran.<br />This research presents a mathematical model for oil and gas optimal allocation to different sectors in Iran using operations research techniques. Sectors are residential and commercial, transportation, industries, agriculture, exports, injection to oil reservoirs and power plans as a secondary energy producer. Optimal allocation of energy resources to end-uses from 2011 to 2021 has been done using a linear programming model regarding lifting of subsidies. The results provide scientific basic for the optimal allocation of energy resources in Iran.This research presents a mathematical model for oil and gas optimal allocation to different sectors in Iran using operations research techniques. Sectors are residential and commercial, transportation, industries, agriculture, exports, injection to oil reservoirs and power plans as a secondary energy producer. Optimal allocation of energy resources to end-uses from 2011 to 2021 has been done using a linear programming model regarding lifting of subsidies. The results provide scientific basic for the optimal allocation of energy resources in Iran.<br />This research presents a mathematical model for oil and gas optimal allocation to different sectors in Iran using operations research techniques. Sectors are residential and commercial, transportation, industries, agriculture, exports, injection to oil reservoirs and power plans as a secondary energy producer. Optimal allocation of energy resources to end-uses from 2011 to 2021 has been done using a linear programming model regarding lifting of subsidies. The results provide scientific basic for the optimal allocation of energy resources in Iran.https://imj.ut.ac.ir/article_57264_f61df5cc295b7bcfb7507af452e80947.pdfUniversity of TehranIndustrial Management Journal2008-58857320150923Strategic analysis of Municipality’s service quality using combination of servperf model and BCG matrix by gray relational analysis methodStrategic analysis of Municipality’s service quality using combination of servperf model and BCG matrix by gray relational analysis method5876065070010.22059/imj.2015.50700FASeyyed HabiballahMirghafooriAssociate Prof.., Industrial Management, Yazd University, Yazd, IranMohammad AliSangborMsc of Industrial Management, Yazd uni., Yazd, Iran0000-0002-1527-3867NegarJalilianMsc of Industrial Management, Yazd uni., Yazd, IranJournal Article20131025Considering the importance of quality services, the study attempted to analyze the quality of municipal services strategy in Yazd. The population of this study, including all client of the area three municipality .of Yazd city from this population, 111 clients were selected to answer the questionnaire. Content validity of the questionnaire was confirmed by experts point of views and the reliability was confirmed regarding coefficient alpha equal to 79/0.The present study, combined the Boston Consulting Group matrix model and Servperf model as a strategic tool to reveal that according to the five dimensions of service quality, the organization how extent has succeeded in customer satisfaction. It also is trying to determine the status of the organization in relation to service quality dimensions. The results of data analysis indicate that, the dimensions of accountability, service assurance and reliability is located in question mark region. In other words, the effect of improving the quality of service in these dimensions is important, but the level of service quality in low.Considering the importance of quality services, the study attempted to analyze the quality of municipal services strategy in Yazd. The population of this study, including all client of the area three municipality .of Yazd city from this population, 111 clients were selected to answer the questionnaire. Content validity of the questionnaire was confirmed by experts point of views and the reliability was confirmed regarding coefficient alpha equal to 79/0.The present study, combined the Boston Consulting Group matrix model and Servperf model as a strategic tool to reveal that according to the five dimensions of service quality, the organization how extent has succeeded in customer satisfaction. It also is trying to determine the status of the organization in relation to service quality dimensions. The results of data analysis indicate that, the dimensions of accountability, service assurance and reliability is located in question mark region. In other words, the effect of improving the quality of service in these dimensions is important, but the level of service quality in low.https://imj.ut.ac.ir/article_50700_27cf98fe9e1df40fd06baeb4657b7820.pdfUniversity of TehranIndustrial Management Journal2008-58857320150923step-by-step Methodology for developing strategy maps: a hybrid approach using quality function deployment, fuzzy screening and fuzzy cognitive mapsstep-by-step Methodology for developing strategy maps: a hybrid approach using quality function deployment, fuzzy screening and fuzzy cognitive maps6076395726510.22059/imj.2015.57265FABijanNahavandiPh.D. in management, Faculty Of Management And Economics, Tarbiat Modares University, Tehran, Iran1111-2222-3333-4444AbbasMoghbel BaarzAssistant Prof., Faculty Of Management And Economics, Tarbiat Modares University, Tehran, IranAdelAzar3. Prof., Faculty Of Management And Economics, Tarbiat Modares University, Tehran, Iran0000-0003-2123-7579Journal Article20140202Nowadays Balanced scorecard has a critical role in implementing strategies for many organizations. Strategy map as the 3rd generation of BSC by inverting mission and vision into strategic objectives is the linkage between formulating and implementing strategies. However, the methodology of developing strategy maps has many ambiguities. This study with inspiring by other authors and exploring literatures representing an improved methodology to resolve three identified short comings or improvement potential. Using QFD and fuzzy screening, fuzzy cognitive maps and considering fuzzy environment a step-by-step methodology represented to considering strategic objective refinement, causal effects modelling and human subjectivities. Finally the methodology has applied in a practical case.Nowadays Balanced scorecard has a critical role in implementing strategies for many organizations. Strategy map as the 3rd generation of BSC by inverting mission and vision into strategic objectives is the linkage between formulating and implementing strategies. However, the methodology of developing strategy maps has many ambiguities. This study with inspiring by other authors and exploring literatures representing an improved methodology to resolve three identified short comings or improvement potential. Using QFD and fuzzy screening, fuzzy cognitive maps and considering fuzzy environment a step-by-step methodology represented to considering strategic objective refinement, causal effects modelling and human subjectivities. Finally the methodology has applied in a practical case.https://imj.ut.ac.ir/article_57265_ffb600f942e59041438ecc60d7b13ecd.pdf