AN EFFICIENT MADM METHOD: ELECTROMAGNETISM-LIKE METHOD FOR SELECTION AND ORDERING

Year 2017, Volume: 35 Issue: 3, 513 - 522, 01.09.2017

Vildan Ç. Özkır Burak Topçu

Abstract

Multiple Attribute Decision Making methods aims to improve the quality of decisions in various fields of management science. Decision makers are mostly faced with new decisions involving conflicting multiple objectives. Practically, these problems include a ranking information including individual/group judgments on a number of pre-determined alternatives with respect to different criteria. This study proposes a new method, called Electromagnetism-like Method for Selection and Ordering, to select the best alternative and/or to determine the rank order of finite number of alternatives. We investigated the performance of proposed method and achieved satisfactory results for many selection and ordering case. The comparative analysis with other multiple criteria decision making methods verifies the performance of the proposed method. The results show that the method is a useful tool to assist decision-makers in terms selection and ordering decisions.

Keywords

Multi-attribute decision analysis, electromagnetism-like heuristics, attraction-repulsion, distance based methods

References

• [1] Aydin, S., Kahraman, C. and İ. Kaya, (2012), “A new fuzzy multicriteria decision making approach: An application for European Quality Award assessment”, Knowledge-Based Systems, 32, 37-46.
• [2] Birbil, Ş.İ. and S-C. Fang, (2003), “An Electromagnetism-like Mechanism for Global Optimization”, Journal of Global Optimization, 25, 263–282.
• [3] Bottani, E. & Rizzi, A., (2006) “A Fuzzy TOPSIS Methodology to Support Outsourcing of Logistics Services", Supply Chain Management: An International Journal”, 11(4), 294-308.
• [4] Chu, T. C., (2002), “Facility Location Selection Using Fuzzy TOPSIS Under Group Decisions”, International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 10, 687-701.
• [5] Debel, D., De Reyck, B., Leus, R. and M. Vanhoucke, (2006), “A hybrid scatter search/electromagnetism meta-heuristic for project scheduling”, European Journal of Operational Research, 169, 638–653.
• [6] Ertugrul.I. and N. Karakasoglu. (2009), “Evaluation of bank branch performances by VIKOR”, Endüstri Mühendisliği Dergisi, 20(1), 19-28.
• [7] Gomes, L. F. A. M. and L. A. D. Rangel, (2009), “An application of the TODIM method to the multicriteria rental evaluation of residential properties”, European Journal of Operational Research, 193(1), 204-211.
• [8] Hwang, C.L. and K. Yoon, (1981), Multiple Attributes Decision Making Methods and Applications, Springer, Berlin Heidelberg.
• [9] Korhonen, P., Wallenius, J. and S. Zionts, (1981), “Solving the discrete multiple criteria problem using convex cones”, Management Science, 30, 1336–1345.
• [10] Maity, S.R., Chatterjee, P. and S. Chakraborty, (2012), "Cutting tool material selection using grey complex proportional assessment method", Materials & Design, 36, 372-378.
• [11] Pomerol, J-C., and S. Barba-Romero, 2000, Multicriterion Decision in Management: Principles and Practice, Kluwer Academic Publishers, Massachusetts, USA.
• [12] Shahanaghi, K. and S.A. Yazdian, (2009), “Vendor Selection Using a New Fuzzy Group TOPSIS Approach”, Journal of Uncertain Systems, 3(3), 221-231.
• [13] Srinivasan V. and A.D. Shocker, (1973), “Linear programming for multidimensional analysis of preferences, Psychometrika, 38, 337-369.
• [14] Tian, J., Yu, D., Yu, B. and S. Ma (2013), “A fuzzy TOPSIS model via chi-square test for information source selection”, Knowledge-Based Systems, 37, 515-527.
• [15] Xu, L. and J-B. Yang, (2001), “Introduction to Multi-Criteria Decision Making and the Evidential Reasoning Approach” Working Paper, No. 0106, Manchester School of Management, U.K.
• [16] Zahedi, F., (1986), “The Analytic Hierarchy Process-A Survey of the Method and its Applications” Interfaces, 16, 96-108.
• [17] Zionts, S., (1978), “Multiple Criteria Problem Solving, Springer.