Vision-based Weighting System (ViWeS) in Prospective MADM

  • Sarfaraz Hashemkhani Zolfani School of Engineering, Catholic University of the North, Coquimbo, Chile
  • Ali Ebadi Torkayesh Faculty of Engineering and Natural Sciences, Sabanci University, Istanbul, Turkey
  • Ramin Bazrafshan Department of Industrial Engineering and Management Systems, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran
Keywords: Prospective Multiple Attribute Decision Making (PMADM), Vision-based weighting system (ViWeS), Evaluation Based on the Distance from the Average Solution (EDAS), Policy-Making, Weighting system

Abstract

Policy-making is an undeniable decision-making process in every company where different kinds of decisions are taken based on different goals and preferences in each vision. “Prospective Multiple Attribute Decision Making (PMADM)” is one of the well-known decision-making frameworks that have been used as a flexible decision-making tool for developing policies and making future decisions over different periods. This study presents a multi attribute problem with three different visions where a decision-making process is required for each vision in order to prioritize the potential set of alternatives. Evaluation Based on the Distance from the Average Solution (EDAS) is used as a MADM model to show the applicability and feasibility of the PMADM framework. A vision-based weighting system (ViWeS) prepares a new opportunity to take proper decisions in different visions and time requirements. This research is analyzed three-time vision (Current, 2025, and 2030) and showed by changing the time, the rank of the alternatives also is changed. In numerical example is indicated in the current vision, Alternative 5 gets rank one and alternative six get rank 2, for 2025 vision, the rank one and two don’t change, and in vision 2030, the rank of one does not change, but the rank of second change from Alternative 6 to 3.

References

Alosta, A., Elmansuri, O., & Badi, I. (2021). Resolving a location selection problem by means of an integrated AHP-RAFSI approach. Reports in Mechanical Engineering, 2(1), pp. 135-142.

Badi, I., Abdulshahed, A. M., & Shetwan, A. (2018). A case study of supplier selection for a steelmaking company in Libya by using the Combinative Distance-based ASsessment (CODAS) model. Decision Making: Applications in Management and Engineering, 1(1),pp. 1-12.

Biswas, T. K., Stević, Ž., Chatterjee, P., & Yazdani, M. (2019). An integrated methodology for evaluation of electric vehicles under sustainable automotive environment. In Advanced multi-criteria decision making for addressing complex sustainability issues (pp. 41-62). IGI Global.

Brans. J.P., (1982). L’ingénièrie de la décision; Elaboration d’instruments d’aide à la décision. La méthode PROMETHEE. In R. Nadeau and M. Landry, editors, L’aide à la décision: Nature, Instruments et Perspectives d’Avenir, pp. 183–213, Québec, Canada, 1982. Presses de l’Université Laval.

Đalić, I., Stević, Ž., Ateljević, J., Turskis, Z., Zavadskas, E. K., & Mardani, A. (2021). A novel integrated MCDM-SWOT-TOWS model for the strategic decision analysis in transportation company. Facta Universitatis, Series: Mechanical Engineering.

Durmić, E., Stević, Ž., Chatterjee, P., Vasiljević, M., & Tomašević, M. (2020). Sustainable supplier selection using combined FUCOM–Rough SAW model. Reports in mechanical engineering, 1(1), pp. 34-43.

Ebadi Torkayesh, A., Fathipoir, F. and Saidi-Mehrabd, M., (2019). Entropy-based multi-criteria analysis of thermochemical conversions for energy recovery from municipal solid waste using fuzzy VIKOR and ELECTRE III: case of Azerbaijan region, Iran. Journal of Energy Management and Technology, 3(1), pp. 17-29.

Ecer, F., (2018). Third-party logistics (3PLs) provider selection via Fuzzy AHP and EDAS integrated model. Technological and Economic Development of Economy, 24(2), 615-634.

Fazlollahtabar, H., & Kazemitash, N. (2021). Green supplier selection based on the information system performance evaluation using the integrated best-worst method. Facta Universitatis, Series: Mechanical Engineering.

Hashemkhani Zolfani, S. and Derakhti, A., (2020). Synergies of Text Mining and Multiple Attribute Decision Making: A Criteria Selection and Weighting System in a Prospective MADM Outline. Symmetry, 12(5), 868.

Hashemkhani Zolfani, S. and Masaeli, R., (2020). From Past to Present and into the Sustainable Future. PMADM Approach in Shaping Regulatory Policies of the Medical Device Industry in the New Sanction Period. Sustainability Modeling in Engineering, pp. 73-95.

Hashemkhani Zolfani, S., Maknoon, R. and Zavadskas, E.K., (2016). An introduction to prospective multiple attribute decision making (PMADM). Technological and Economic Development of Economy, 22(2), pp. 309-326.

Hashemkhani Zolfani, S., Yazdani, M., Ebadi Torkayesh, A. and Derakhti, A., (2020). Application of a Gray-Based Decision Support Framework for Location Selection of a Temporary Hospital during COVID-19 Pandemic. Symmetry, 12(6), 886.

Hwang, C.L., Yoon, K., (1981). Multiple Attribute Decision Making: Methods and Applications. New York: Springer-Verlag.

Ignatius, J., Rahman, A., Yazdani, M., Šaparauskas, J. and Haron, S.H., (2016). An integrated fuzzy ANP–QFD approach for green building assessment. Journal of Civil Engineering and Management, 22(4), pp.551-563.

Keshavarz Ghorabaee, M., Zavadskas, E.K., Olfat, L. and Turskis, Z., (2017). Multi-criteria inventory classification using a new method of evaluation based on distance from average solution (EDAS). Informatica, 26(3), pp.435-451.

Kumar, A., Sah, B., Singh, A. R., Deng, Y., He, X., Kumar, P., and Bansal, R. C., (2017). A review of multi criteria decision making (MCDM) towards sustainable renewable energy development. Renewable and Sustainable Energy Reviews, 69, 596-609.

Li, Y. Y., Wang, J. Q., & Wang, T. L., 2019. A linguistic neutrosophic multi-criteria group decision-making approach with EDAS method. Arabian Journal for Science and Engineering, 44(3), 2737-2749.

Mardani, A., Zavadskas, E. K., Khalifah, Z., Jusoh, A., and Nor, K. M., (2016). Multiple criteria decision-making techniques in transportation systems: A systematic review of the state of the art literature. Transport, 31(3), 359-385.

Opricovic S., (1988). Multicriteria optimization in civil engineering systems. PhD Thesis, 302 Faculty of Civil Engineering, Belgrade.

Pamučar, D. S., & Savin, L. M. (2020). Multiple-criteria model for optimal off-road vehicle selection for passenger transportation: BWM-COPRAS model. Vojnotehnički glasnik, 68(1), 28-64.

Radović, D., & Stević, Ž. (2018). Evaluation and selection of KPI in transport using SWARA method. Transport & Logistics: The International Journal, 8(44), 60-68.

Stević, Ž., Tanackov, I., Vasiljević, M., & Vesković, S. (2016, September). Evaluation in logistics using combined AHP and EDAS method. In Proceedings of the XLIII International Symposium on Operational Research, Belgrade, Serbia (pp. 20-23).

Torkayesh, S. E., Amiri, A., Iranizad, A., and Torkayesh, A. E., (2020). Entropy based EDAS decision making model for neighborhood selection: A case study in Istanbul. Journal of Industrial Engineering and Decision Making, 1(1), 1-11.

Yazdani, M., Chatterjee, P., Zavadskas, E.K. and Zolfani, S.H., (2017). Integrated QFD-MCDM framework for green supplier selection. Journal of Cleaner Production, 142, pp.3728-3740

Zolfani, S.H., Zavadskas, E.K., Khazaelpour, P. and Cavallaro, F., (2018). The multi-aspect criterion in the PMADM outline and its possible application to sustainability assessment. Sustainability, 10(12), 4451.

Published
2021-07-08
How to Cite
Hashemkhani Zolfani, S., Torkayesh, A. E., & Bazrafshan, R. (2021). Vision-based Weighting System (ViWeS) in Prospective MADM. Operational Research in Engineering Sciences: Theory and Applications, 4(2), 140-150. https://doi.org/10.31181/oresta20402140z