A decision support system for multiple criteria alternative ranking using TOPSIS and VIKOR in fuzzy and nonfuzzy environments

被引:54
|
作者
Ploskas, Nikolaos [1 ]
Papathanasiou, Jason [2 ]
机构
[1] Univ Western Macedonia, Dept Informat & Telecommun Engn, Karamanli & Lygeris Str, Kozani 50100, Greece
[2] Univ Macedonia, Dept Business Adm, Thessaloniki 54636, Greece
关键词
Multiple attribute decision making; Fuzzy aggregation operators; Defuzzification; Fuzzy distance metrics; Group decision making; THE-ART SURVEY; COMPROMISE SOLUTION; SELECTION; NUMBERS; COMMUNITIES; EXTENSION; VARIABLES; DISTANCE; MODELS; CHOICE;
D O I
10.1016/j.fss.2019.01.012
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
TOPSIS and VIKOR are two well-known and widely-used multiple attribute decision making methods. Many extensions of these methods have been proposed that either use different techniques to rank alternatives or utilize fuzzy logic to handle alternatives and criteria that are unquantifiable and/or incomplete. In this paper, we present the implementation of a web-based decision support system that incorporates TOPSIS and VIKOR to solve multicriteria decision making problems either in a nonfuzzy or in a fuzzy environment. The aim of this paper is to present a tool that will be used by decision makers to compare various alternative solutions and understand how robust a decision will be. The proposed system can be used both in single and in group decision making problems. In addition, we review several variations for each step of these methods and implement different techniques when applicable. Hence, decision makers can experiment with different techniques in each method. We implement ten normalization techniques, three methods for the calculation of the ideal and anti-ideal solutions, fifteen distance metrics, five fuzzy distance metrics, and eight defuzzification techniques. An illustrative example is presented to highlight the key features of the implemented system and the different scenarios that can be built using the proposed DSS. (C) 2019 Elsevier B.V. All rights reserved.
引用
收藏
页码:1 / 30
页数:30
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