• • 上一篇    

考虑决策者期望和失望-欣喜感知的风险型多属性群决策方法

曹萍萍1, 郑瑾2, 刘小2, 李铭洋2, 王欣艳3   

  1. 1. 中国刑事警察学院基础教研部, 沈阳 110854;
    2. 辽宁大学商学院, 沈阳 110136;
    3. 应急管理部大数据中心, 北京 100013
  • 收稿日期:2022-09-14 修回日期:2022-11-06 发布日期:2023-05-18
  • 通讯作者: 李铭洋, Email:lmy_lnu@163.com
  • 基金资助:
    教育部人文社会科学研究规划基金项目(19YJA630037), 辽宁省社会科学规划基金重点项目(L17AGL001, L20AGL008)资助课题.

曹萍萍, 郑瑾, 刘小, 李铭洋, 王欣艳. 考虑决策者期望和失望-欣喜感知的风险型多属性群决策方法[J]. 系统科学与数学, 2023, 43(4): 1021-1038.

CAO Pingping, ZHENG Jin, LIU Xiao, LI Mingyang, WANG Xinyan. Multiple Attribute Risk Group Decision Making Method Considering Expectations and Disappointment-Elation of Decision Makers[J]. Journal of Systems Science and Mathematical Sciences, 2023, 43(4): 1021-1038.

Multiple Attribute Risk Group Decision Making Method Considering Expectations and Disappointment-Elation of Decision Makers

CAO Pingping1, ZHENG Jin2, LIU Xiao2, LI Mingyang2, WANG Xinyan3   

  1. 1. Department of Basic Teaching and Research, Criminal Investigation Police University of China, Shenyang 110854;
    2. Business School, Liaoning University, Shenyang 110136;
    3. Communication and Information Center, Ministry of Emergency Management, Beijing 100013
  • Received:2022-09-14 Revised:2022-11-06 Published:2023-05-18
针对多个决策者给出属性期望且存在多种类型属性值的风险型多属性决策问题, 提出一种基于失望理论的风险型多属性决策方法. 文章首先依据决策者的期望矩阵和风险决策矩阵构建针对各决策者的损益矩阵; 其次,在考虑决策者失望-欣喜感知的情境下,依据失望理论将损益矩阵转化为修正决策矩阵, 并利用PROMETHEE-II方法构建出偏好函数; 然后,依据偏好函数值计算出各自然状态下针对各决策者的排序值; 在此基础上,借助自然状态发生的概率和决策者权重计算出各备选方案的总体排序值,据此对各备选方案进行排序; 最后,通过一个算例说明了该方法的可行性和有效性.
This paper proposes a decision analysis method based on disappointment theory to solve multiple attribute risk decision making problems with attribute expectations given by decision makers and multiple forms of attribute values. In this paper, the matrix with gains or losses relative to each decision maker is built according to expectation matrix of decision-makers and risk decision matrix. Then, taking into account disappointment-elation of decision makers, the matrix with gains or losses is transformed to the modified decision matrix based on disappointment theory, and the preference function is constructed using the PROMETHEE-II method. Furthermore, the ranking value for each decision maker in each natural state is calculated according to the preference function values. On this basis, the overall ranking value of each alternative is calculated based on the probability of natural state occurrence and the weights of the decision makers, and the ranking results of the alternatives can be obtained according to the overall ranking values. Finally, a numerical example is used to illustrate the feasibility and validity of the proposed method.

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