概率犹豫模糊环境下基于前景理论和TOPSIS法的多属性群决策模型
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O225

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Multi-attribute Group Decision Making Model Based on Prospect Theory and TOPSIS in Probabilistic Hesitating Fuzzy Environment
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    摘要:

    在研究多属性群决策问题的领域中,概率犹豫模糊术语集作为犹豫模糊集的一种扩展,正广受关注。针对目前在概率犹豫模糊语言环境下,考虑用主客观结合的方式来求解权重以及对方案排序的过程中存在的问题,本文提出了一种基于前景理论和逼近理想解排序法(TOPSIS)相结合的多属性群决策模型。首先根据已知的主观决策者权重,经过一致性调节运算得到决策者的综合权重;其次利用熵值法构建了属性权重的求解模型;在充分考虑决策者心理行为的前提下,求解出正、负理想解矩阵,并且基于TOPSIS方法实现多个备选方案之间的优劣排序;最后,通过实例验证了该模型的可行性和有效性。

    Abstract:

    In the field of studying multi-attribute group decision-making problems,the hesitant probabilistic fuzzy set (HPFS), as an extension of fuzzy numbers, has received much attention. Under the probabilistic hesitant fuzzy language environment, the combination of subjective and objective methods to solve the problems in the process of solving weights and sorting schemes is considered, which is more suitable for depicting the DMs’ preferences in the decision-making process. Consequently, a multi-attribute group decision-making model based on the combination of prospect theory and TOPSIS method is proposed in this paper. First, the comprehensive weights of the decision-makers are obtained through the consistency adjustment calculation. Secondly, the solution model of the attribute weights is constructed by using the entropy method. Under the premise of fully considering the psychological behavior of decision makers, the positive and negative ideal solution matrices are solved. And the pros and cons of multiple alternatives are ranked based on the TOPSIS method. Finally, an established case example is applied to validate the applicability and validity of the proposed method.

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王志平,傅敏,王沛文. 概率犹豫模糊环境下基于前景理论和TOPSIS法的多属性群决策模型[J]. 科学技术与工程, 2022, 22(4): 1329-1337.
Wang Zhiping, Fu Min, Wang Peiwen. Multi-attribute Group Decision Making Model Based on Prospect Theory and TOPSIS in Probabilistic Hesitating Fuzzy Environment[J]. Science Technology and Engineering,2022,22(4):1329-1337.

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历史
  • 收稿日期:2021-05-18
  • 最后修改日期:2021-11-09
  • 录用日期:2021-10-11
  • 在线发布日期: 2022-01-28
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