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Issue title: ICNC-FSKD 2015
Guest editors: Zheng Xiao and Kenli Li
Article type: Research Article
Authors: Lv, Zhi-Yinga; b; * | Zheng, Li-Weic | Liang, Xi-Nongd | Liang, Xue-Zhange
Affiliations: [a] College of Management, Chengdu University of Information Technology, Chengdu, China | [b] College of Mathematics, University of Electronic Science and Technology of China, Chengdu, China | [c] College of Applied Mathematics, Chengdu University of Information Technology, Chengdu, China | [d] Jilin Province Road Administration Bureau, Changchun, China | [e] College of Mathematics, Jilin University, Changchun, China
Correspondence: [*] Corresponding author. Zhi-Ying Lv, Tel.: +86 13688326955; E-amil: [email protected].
Abstract: A fuzzy multiple attribute decision making method is investigated, there the weights are given by interval numbers, the qualitative attribute values are first given by linguistic terms and then are represented as the form of triangular fuzzy numbers, and the quantitative attribute values are given by the form of triangular fuzzy numbers. A possibility degree formula for the comparison between two trapezoidal fuzzy numbers is proposed. Then, using this possibility degree formula, possibility degree matrices are built and the central dominance of one alternative outranking all other alternatives is defined under one attribute. According to the ordered weighted average (OWA) operator, an approach is presented to aggregate the possibility degree matrices based on attributes and then the most desirable alternative is selected. This fuzzy multiple attribute decision making method is used in the field of financial investment evaluation, and the set of attributes of the decision making program is built by financial analyses and accounting reports in the same industry. Finally, numerical example is provided to demonstrate the practicality and the feasibility of the proposed method.
Keywords: Possibility degree, multiple attribution decision making, trapezoidal fuzzy number, investment options, OWA operators
DOI: 10.3233/JIFS-169010
Journal: Journal of Intelligent & Fuzzy Systems, vol. 31, no. 2, pp. 787-794, 2016
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