Developing a fuzzy TOPSIS method based on alpha level sets

• Main Authors: Chia Chih Tsai, 蔡嘉芝
• Other Authors: T. Y. Chen
• Format: Others
• Published: 2010
• Online Access: http://ndltd.ncl.edu.tw/handle/31586227217480786494

碩士 === 長庚大學 === 工商管理學系 === 98 === With the technology developing and economy changing, decision-makers have no choice but to deal with multi-criteria issues, and which give rise to the MCDM problems. The decision criteria are very hard to be measured and analyzed because of the nature of the criteria. In order to integrate all possible criteria into one single analysis model, this research proposes a fuzzy TOPSIS method based on alpha level sets, based on the MCDM literature and fuzzy theory, and demonstrate the efficiency of this proposed model by using two different application cases. To better present the vagueness of the related-information during the decision-making process, the weights of the criteria and the evaluation value of the alternatives of the proposed decision-making model in our research are characterized by linguistic term and the linguistic variables are showed by trapezoidal fuzzy number. Based on the above principle, this research suggests the following decision-making steps: Firstly, determine the importance of the criteria by using linguistic variables. Secondly, form a decision matrix and normalize the decision matrix based on the first step. Thirdly, calculate the weighted normalized decision matrix and determine the ideal and negative-ideal solutions. Fourthly, calculate the relative closeness of each alternative to the ideal solution based on different alpha level sets. Finally, rank the alternatives according to the relative closeness to the ideal solution based on average level sets. In order to examine the efficiency of our decision model, this research demonstrates how to incorporate linguistic variables into the fuzzy multiple criteria decision making process and provides the evidence for the above process by using three different application cases (Selecting dental material supplier of implantation and selecting the location of the distribution center). The proposed fuzzy TOPSIS method based on alpha level sets complied with interval estimate approach and generalized fuzzy number adopting the alpha level sets and extension principle to propose a non-linear programming model by considering both cost and benefit criteria to evaluates all the possible alternatives according to the relative closeness to the ideal solution based on average level sets, which can provide more information to decision makers.