Strategic weight manipulation in fuzzy multiple attribute decision making

被引:0
|
作者
Zhao M. [1 ]
Qin J.-L. [1 ]
Pan Y.-R. [1 ]
Wu W.-T. [2 ]
机构
[1] School of Management, Northeastern University at Qinhuangdao, Qinhuangdao
[2] School of Management, University of Science and Technology of China, Hefei
来源
Kongzhi yu Juece/Control and Decision | 2021年 / 36卷 / 05期
关键词
Approach degree; Fuzzy multiple attribute decision making; Interval number; Possibility degree; Ranking range; Strategic weight manipulation; Triangular fuzzy number;
D O I
10.13195/j.kzyjc.2019.0542
中图分类号
学科分类号
摘要
In a real multi-attribute decision making problem, the decision maker can strategically set the attribute weights to obtain the desired alternative ranking, which is the manipulation problem of strategic weight. The dishonesty of decision-makers is ubiquitous in reality, and the research on this problem has practical value. At present, the research on this problem mainly focuses on the crisp number. In view of this, the paper extends the research on strategy weight manipulation to fuzzy multi-attribute decision making. Firstly, the concept of strategy weight control and rank range for fuzzy multi-attribute decision making are defined. Then, a hybrid linear programming model based on the possibility and proximity formula is proposed to obtain the ranking range, and the optimal model of decision-maker's policy weight vector is established. Finally, the multi-attribute decision making problems with decision evaluation information as interval number and triangular fuzzy number are taken as examples to verify the feasibility and practicability of the proposed model. The results show that the (ordered weighted averaging, OWA) operator has stronger resistance to the manipulation of strategic weight, and the expanded model maintains the superiority and accuracy of the alternative ranking model under the evaluation information of original crisp number. Copyright ©2021 Control and Decision.
引用
收藏
页码:1259 / 1267
页数:8
相关论文
共 22 条
  • [1] Ziemba P., Neat F-promethee——A new fuzzy multiple criteria decision making method based on the adjustment of mapping trapezoidal fuzzy numbers, Expert Systems with Applications, 110, pp. 363-380, (2018)
  • [2] Liang D C, Xu Z S., The new extension of TOPSIS method for multiple criteria decision making with hesitant pythagorean fuzzy sets, Applied Soft Computing, 60, pp. 167-179, (2017)
  • [3] Qin Q, Liang F Q, Li L, Et al., A TODIM-based multi-criteria group decision making with triangular intuitionistic fuzzy numbers, Applied Soft Computing, 55, pp. 93-107, (2017)
  • [4] Li G X, Peng Y, Kou G., Dynamic multiple criteria decision making method with uncertain power geometric weighted average operators, Systems Engineering——Theory and Practice, 35, 7, pp. 1855-1862, (2015)
  • [5] Feng X Q, Liu Q, Wei C P., Hesitant fuzzy 2-tuple linguistic multiple attribute decision making method, Operations Research and Management Science, 1, pp. 17-22, (2018)
  • [6] Huang Z L, Luo J., Possibility degree programming model for uncertain multi-attribute decision making and its application, Control and Decision, 32, 1, pp. 131-140, (2017)
  • [7] Xu Z S., A method based on objective similarity scale for multi-objective decision-making, Systems Engineering——Theory & Practice, 21, 9, pp. 101-104, (2001)
  • [8] Liu Z X, Liu S F, Fang Z G., Decision making model of grey comprehensive correlation and relative close degree based on kernel and greyness degree, Control and Decision, 32, 8, pp. 1475-1480, (2017)
  • [9] Lan J B, Xu Y, Huo L A, Et al., Research on the priorities of fuzzy analytical hierarchy process, Systems Engineering——Theory and Practice, 26, 9, pp. 107-112, (2006)
  • [10] Zhang Z G, Sheng Y, Ou C., The method of determining the weight of the index based on FAHP-CEEMDAN, Statistics and Decision, 35, 2, pp. 81-85, (2019)