The indifference points in multi-criteria decision problems
(case stady Evalution Supplyers in Zanjan Province Water and Wastewater Company)
Subject Areas :
Industrial Management
Reza Radfar
1
,
ARSHAD FARAHMANDIAN
2
,
Mohammad Ali Afshar Kazemi
3
1 - Technology Management, Faculty of Management and Economy, Azad University of Science and Research, Tehran, Iran
2 - Department of Industrial Management, Science and Research Branch, Islamic Azad University, Tehran, Iran.
3 - Associate Professor.,Department of Industrial Management, Science and Research Branch, Islamic Azad University, Tehran, Iran.
Received: 2018-12-30
Accepted : 2019-06-02
Published : 2019-09-19
Keywords:
Indifference Points,
Parallel Matrixs,
Marginal Rate of Substitution,
Metaheuristic Algorithms,
Abstract :
Decisions on the process of assessment and selection of suppliers should be made by examining all possible options, otherwise the organization will encounter many problems during the implementation and implementation phases.The purpose of the present study was to determine the indifference points of assessors of the water and wastewater company in Zanjan province.The method of this study was descriptive. The data of this study is related to supplier assessment of one of the projects of the city water and wastewater company Zanjan province.The data was collected based on the views of 10 experts with at least a bachelor's degree and at least 5 years of work experience in the company based on the "supplier assessment form".The data has been analyzed using the 2014 version of MATLAB software.A total of 10 cases of matrix matched with the initial decision matrix are identified and generated separately for each method.TOPSIS-GA = 2 and TOPSIS-PSO = 3 and AHP-GA = 2 and AHP-PSO = 3. A total of 10 cases of matrix matched with the initial decision matrix are identified and generated separately for each method.
References:
Alborzi, M. (2008) .Augmenting System Dynamics with Genetic Algorithm andTopsis Multivariate Ranking Module for Multi-Criteria Optimization. Proceedings ofthe International Conference of the System Dynamics Society.
Ali, R. (2017). Principleof Management. Tehran: Samat Publication.
Asgharpour, M. J. 2017. Multiple Criteria Decision Making, Tehran University
Chen, D., Zhou, Z. & Pham, D. (2008). Research onthe Grey Relational Evaluation Method of Core Competencies of Virtual Enterprise Members. Kybernetes, 37, 1250-1256.
Faghih, N., Montazeri, M. M. (2008), Genetic Algorithms for Assembly Line Balancing Problem. Journal of Industrial Management, 1(1), 107-124.
Hwang, Y., A. & Wang, B., S. (2016). A Matrix Approach to the Associated Consistency With Respect to the Equal Allocation of Non-Separable Costs. Operations Research Letters, 44, 826-830.
Intriligator, M. D. (1971). Mathematical Optimization and Economic Theory.Phi Learning; 1st edition.
Leili, M, M. S., Ekradi, E, Parvin, E., Fazeli, H. (2017). Studying the Relationship between Managers' Decision Making Styles withThe Level Of Creativity And Participative Management In Guidance Schools. InnovCreat Hum Sci Journal, 4, 19.
Mohamadi, A, M. S., Dostmohammadi, A., Khaleghi, A.(2015). Management Assessment and Selection of Logistics Providers atthe Social Security Hospital of Imam Hossein in Zanjan. International Conference on Management. Istanbul, Turkey.
Mulliner, E., Malys, N. & Maliene, V. (2016). Comparative Analysis ofMcdm Methods forthe Assessment Of Sustainable Housing Affordability. Omega, 59, 146-156.
Radfar, R, K. N. (2015). Identify And Ranking The Factors Affecting The Efficiency Of Using By Dematel. Productivity Management Journal, 35, 19.
Salati F, M. A. (2014). Offer The Value Function (Utility) To Prioritize Research Projects In R & D Centers Using The UtaMethod (Case of Water Resources Company In Iran). Industrial Management Studies, 31, 19-33.
Serrai, W., Abdelli, A., Mokdad, L. & Hammal, Y. (2017). Towards An Efficient And A More Accurate Web Service Selection Using Mcdm Methods. Journal of Computational Science, 22, 253-267.
Shahbazi, L. (2016). At The Same Time Optimize The Planning Problem-Labor-Service Equipment Using Particle Swarm Algorithm. Ms. Thesis,Islamic Azad University, Zanjan Branch.
Taboli, M.(2012). New Method For Solving Multi-Criteria Decision. Industrial Management Studies, 9, 20.
Yang, X.S., (2011). Metaheuristic Optimization. Scholarpedia, 6, 11472.
Yu, X., Zhang, S., Liao, X. & Qi, X. (2018). Electre Methods in Prioritized Mcdm Environment. Information Sciences, 424, 301-316.
Nath, P., Nachiappan, S., & Ramanathan, R. (2019). A heuristics approach for computing the largest eigenvalue of a pairwise comparison matrix. International Journal of Operational Research (IJOR), Vol. 34, No. 4,
Schiffels, S., Fliedner, T., & Kolisch, R. (2018). Human behavior in project portfolio selection: Insights from an experimental study. Decision Sciences, 49(6), 1061-1087.
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Alborzi, M. (2008) .Augmenting System Dynamics with Genetic Algorithm andTopsis Multivariate Ranking Module for Multi-Criteria Optimization. Proceedings ofthe International Conference of the System Dynamics Society.
Ali, R. (2017). Principleof Management. Tehran: Samat Publication.
Asgharpour, M. J. 2017. Multiple Criteria Decision Making, Tehran University
Chen, D., Zhou, Z. & Pham, D. (2008). Research onthe Grey Relational Evaluation Method of Core Competencies of Virtual Enterprise Members. Kybernetes, 37, 1250-1256.
Faghih, N., Montazeri, M. M. (2008), Genetic Algorithms for Assembly Line Balancing Problem. Journal of Industrial Management, 1(1), 107-124.
Hwang, Y., A. & Wang, B., S. (2016). A Matrix Approach to the Associated Consistency With Respect to the Equal Allocation of Non-Separable Costs. Operations Research Letters, 44, 826-830.
Intriligator, M. D. (1971). Mathematical Optimization and Economic Theory.Phi Learning; 1st edition.
Leili, M, M. S., Ekradi, E, Parvin, E., Fazeli, H. (2017). Studying the Relationship between Managers' Decision Making Styles withThe Level Of Creativity And Participative Management In Guidance Schools. InnovCreat Hum Sci Journal, 4, 19.
Mohamadi, A, M. S., Dostmohammadi, A., Khaleghi, A.(2015). Management Assessment and Selection of Logistics Providers atthe Social Security Hospital of Imam Hossein in Zanjan. International Conference on Management. Istanbul, Turkey.
Mulliner, E., Malys, N. & Maliene, V. (2016). Comparative Analysis ofMcdm Methods forthe Assessment Of Sustainable Housing Affordability. Omega, 59, 146-156.
Radfar, R, K. N. (2015). Identify And Ranking The Factors Affecting The Efficiency Of Using By Dematel. Productivity Management Journal, 35, 19.
Salati F, M. A. (2014). Offer The Value Function (Utility) To Prioritize Research Projects In R & D Centers Using The UtaMethod (Case of Water Resources Company In Iran). Industrial Management Studies, 31, 19-33.
Serrai, W., Abdelli, A., Mokdad, L. & Hammal, Y. (2017). Towards An Efficient And A More Accurate Web Service Selection Using Mcdm Methods. Journal of Computational Science, 22, 253-267.
Shahbazi, L. (2016). At The Same Time Optimize The Planning Problem-Labor-Service Equipment Using Particle Swarm Algorithm. Ms. Thesis,Islamic Azad University, Zanjan Branch.
Taboli, M.(2012). New Method For Solving Multi-Criteria Decision. Industrial Management Studies, 9, 20.
Yang, X.S., (2011). Metaheuristic Optimization. Scholarpedia, 6, 11472.
Yu, X., Zhang, S., Liao, X. & Qi, X. (2018). Electre Methods in Prioritized Mcdm Environment. Information Sciences, 424, 301-316.
Nath, P., Nachiappan, S., & Ramanathan, R. (2019). A heuristics approach for computing the largest eigenvalue of a pairwise comparison matrix. International Journal of Operational Research (IJOR), Vol. 34, No. 4,
Schiffels, S., Fliedner, T., & Kolisch, R. (2018). Human behavior in project portfolio selection: Insights from an experimental study. Decision Sciences, 49(6), 1061-1087.
