Multi-attribute decision-making method based on the reconciled hesitant fuzzy information

被引：0
|
作者：
Fang B. [1 ]
Han B. [1 ]
Zhu J. [1 ]
机构：
[1] Army Command College of PLA, Nanjing
来源：
Kongzhi yu Juece/Control and Decision | 2022年 / 37卷 / 10期
关键词：
aggregation operator; distance measure; entropy measure; hesitant fuzzy elements; probabilistic hesitant fuzzy elements; reconciled hesitant fuzzy elements;
D O I：
10.13195/j.kzyjc.2021.0328
中图分类号：
学科分类号：
摘要：
It has been found that hesitant fuzzy information and probabilistic hesitant fuzzy information have some problems with calculating, such as cumbersome calculations and incompatibility with quantitative calculation rules. In this work, we propose a set of solutions, based on the reconciled hesitant fuzzy elements (RHFEs), to solve these problems. By defining the RHFEs as a set of probabilistic hesitant fuzzy elements (PHFEs) with the same probability distribution, this work bridges the gap between hesitant fuzzy information and probabilistic hesitant fuzzy information, and incorporates them into a unified processing framework. Based on this, we build a reconciled hesitant fuzzy multi-attribute decision-making (MADM) method, by developing the operation rules, the information aggregation operators, the distance measures and the hybrid entropy measure for RHFEs, and further apply it to evaluate the command and control (C2) capability of the army’s combined brigades. Numerical experiments show that the theory of reconciled hesitant fuzzy decision-making overcomes the shortcomings of existing theories, and has some advantages of controllable calculations, easy to program and compatible with quantitative calculation rules. © 2022 Northeast University. All rights reserved.
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页码：2657 / 2666
页数：9
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共 18 条
  • [1] Zadeh L A., Fuzzy sets, Information and Control, 8, 3, pp. 338-353, (1965)
  • [2] Torra V., Hesitant fuzzy sets, International Journal of Intelligent Systems, 25, 6, pp. 529-539, (2010)
  • [3] Xu Z S, Zhao H., Hesitant fuzzy sets theory and applications, pp. 308-382, (2018)
  • [4] Xu Z S, Zhou W., Consensus building with a group of decision makers under the hesitant probabilistic fuzzy environment, Fuzzy Optimization and Decision Making, 16, 4, pp. 481-503, (2017)
  • [5] Gao J, Xu Z S, Liao H C., A dynamic reference point method for emergency response under hesitant probabilistic fuzzy environment, International Journal of Fuzzy Systems, 19, 5, pp. 1261-1278, (2017)
  • [6] Tian X L, Xu Z S, Fujita H., Sequential funding the venture project or not? A prospect consensus process with probabilistic hesitant fuzzy preference information, Knowledge-Based Systems, 161, pp. 172-184, (2018)
  • [7] Zhou W, Xu Z S., Expected hesitant VaR for tail decision making under probabilistic hesitant fuzzy environment, Applied Soft Computing, 60, pp. 297-311, (2017)
  • [8] Wu W Y., Research on group decision making methods with generalized probabilistic hesitant fuzzy information and their applications in supplier selection, (2019)
  • [9] Jiang F J, Ma Q G., Multi-attribute group decision making under probabilistic hesitant fuzzy environment with application to evaluate the transformation efficiency, Applied Intelligence, 48, 4, pp. 953-965, (2018)
  • [10] Zhou X L, Ma Q G., Probabilistic hesitant fuzzy algorithm and its application for selection method of network public opinion prediction model, Computer Engineering and Applications, 55, 4, pp. 179-184, (2019)
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