Extension of TOPSIS Method and its Application in Investment

被引:18
作者
Huang, Yubo [1 ]
Jiang, Wen [2 ]
机构
[1] Northwestern Polytech Univ, Sch Automat, Xian 710072, Shaanxi, Peoples R China
[2] Northwestern Polytech Univ, Sch Elect & Informat, Xian 710072, Shaanxi, Peoples R China
基金
中国国家自然科学基金;
关键词
TOPSIS; MCDM; Optimism coefficient; IFWA operator; Investment; DECISION-MAKING; FAILURE MODE; VIKOR METHOD; FUZZY; SELECTION; NUMBERS; MCDM;
D O I
10.1007/s13369-017-2736-3
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Technique for order preference by similarity to an ideal solution (TOPSIS) is an effective technique to solve multi-criteria decision-making problem. It aims to select the alternative, which has the "shortest distance" from positive ideal solution (PIS) and the "farthest distance" from negative ideal solution (NIS). Nevertheless, much literature has demonstrated that the solution calculated by TOPSIS only is the compromise of PIS and NIS, and it is of great restriction in dealing with the practical problems which have diverse demands and properties. Therefore, in the presented model, an optimism coefficient is defined to expand the physical meaning of the standard TOPSIS. Decision-makers (DMs) can describe their attitudes toward risk and profit by changing the value of optimism coefficient. Furthermore, intuitionistic fuzzy number is introduced to measure the evaluations (linguistic values) of DMs to alternatives under diverse criteria. Intuitionistic fuzzy weighted averaging operator is used for fusing the judgments of all DMs. Finally, a conclusion can be safely obtained that the proposed model is stable and validity from the illustrative examples and sensitivity analysis.
引用
收藏
页码:693 / 705
页数:13
相关论文
共 57 条
  • [11] Extension of VIKOR method in intuitionistic fuzzy environment for robot selection
    Devi, Kavita
    [J]. EXPERT SYSTEMS WITH APPLICATIONS, 2011, 38 (11) : 14163 - 14168
  • [12] A Modified TOPSIS Method Based on D Numbers and Its Applications in Human Resources Selection
    Fei, Liguo
    Hu, Yong
    Xiao, Fuyuan
    Chen, Luyuan
    Deng, Yong
    [J]. MATHEMATICAL PROBLEMS IN ENGINEERING, 2016, 2016
  • [13] Optimal site selection of electric vehicle charging station by using fuzzy TOPSIS based on sustainability perspective
    Guo, Sen
    Zhao, Huiru
    [J]. APPLIED ENERGY, 2015, 158 : 390 - 402
  • [14] A modified weighted TOPSIS to identify influential nodes in complex networks
    Hu, Jiantao
    Du, Yuxian
    Mo, Hongming
    Wei, Daijun
    Deng, Yong
    [J]. PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2016, 444 : 73 - 85
  • [15] New Hybrid Multiple Attribute Decision-Making Model for Improving Competence Sets: Enhancing a Company's Core Competitiveness
    Huang, Kuan-Wei
    Huang, Jen-Hung
    Tzeng, Gwo-Hshiung
    [J]. SUSTAINABILITY, 2016, 8 (02)
  • [16] Hwang C. L., 1995, MULTIPLE ATTRIBUTE D, V186
  • [17] An algorithmic method to extend TOPSIS for decision-making problems with interval data
    Jahanshahloo, G. R.
    Lotfi, F. Hosseinzadeh
    Izadikhah, M.
    [J]. APPLIED MATHEMATICS AND COMPUTATION, 2006, 175 (02) : 1375 - 1384
  • [18] Optimal Supply Vendor Selection Model for LNG Plant Projects Using Fuzzy-TOPSIS Theory
    Jang, Woosik
    Hong, Hwa-Uk
    Han, Seung H.
    Baek, Seung Won
    [J]. JOURNAL OF MANAGEMENT IN ENGINEERING, 2017, 33 (02)
  • [19] Failure mode and effects analysis based on a novel fuzzy evidential method
    Jiang, Wen
    Xie, Chunhe
    Zhuang, Miaoyan
    Tang, Yongchuan
    [J]. APPLIED SOFT COMPUTING, 2017, 57 : 672 - 683
  • [20] A modified combination rule in generalized evidence theory
    Jiang, Wen
    Zhan, Jun
    [J]. APPLIED INTELLIGENCE, 2017, 46 (03) : 630 - 640