Plant location selection based on fuzzy TOPSIS
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The selection of plant location plays a very important role in minimizing cost and maximizing the use of resources for many companies. In this paper, a new TOPSIS approach for selecting plant location under linguistic environments is presented, where the ratings of various alternative locations under various criteria, and the weights of various criteria are assessed in linguistic terms represented by fuzzy numbers. To avoid complicated fuzzy arithmetic operations, the linguistic variables, which are represented by triangular fuzzy numbers, are transformed into crisp numbers based on graded mean representation. The canonical representation of multiplication operations on triangular fuzzy numbers is used to obtain the “positive ideal solution” and the “negative ideal solution”. The closeness efficient is defined to determine the ranking order of all alternatives by calculating the distance to both the “positive-ideal solution” and the “negative-ideal solution” simultaneously. Compared with existing fuzzy TOPSIS methods, the proposed method can deal with group decision-making problems in a more efficient manner. A numerical example of plant location selection is used to illustrate the efficiency of the proposed method.
KeywordsDecision-making Plant location selection TOPSIS Triangular fuzzy number
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- 2.Hwang CL, Yoon K (1981) Multiple attribute decision making: methods and applications. Springer, Berlin Heidelberg New YorkGoogle Scholar
- 6.Chu TC (2002) Facility location selecting using fuzzy TOPSIS under group decision. Int J Uncertainty Fuzziness Knowl-Based Syst 10:687–701Google Scholar
- 8.Kauffman A, Gupta MM (1985) Introduction of fuzzy arithmetic: Theory and applications. Van Nostrand, New YorkGoogle Scholar
- 9.Zimmermann HJ (1991) Fuzzy set theory and its applications. Kluwer, BostonGoogle Scholar
- 14.Chen CT (2001) Applying linguistic decision-making method to deal with service quality evaluation problems. Int J Uncertainty Fuzziness Knowl-Based Syst 9:103–114Google Scholar