计算机科学与技术

冲突的区间信念结构下基于证据推理规则的群决策方法

展开
  • 1. 福州大学 决策科学研究所,福建 福州 350116; 2. 福州大学 空间数据挖掘与信息共享省部共建教育部重点实验室,福建 福州 350116; 3. 铜陵学院 建筑工程学院,安徽 铜陵 244061; 4. 福建商学院 信息工程学院,福建 福州 350506

张兴贤(1984-),男,博士生,主要从事决策理论与方法研究。E-mail:307527397@qq.com

收稿日期: 2019-10-31

  修回日期: 2020-01-10

  网络出版日期: 2020-06-01

基金资助

国家自然科学基金资助项目 (61773123); 国家社会科学基金资助项目 (19BGL016); 福建省高校 “新世纪优秀人才支持计划”项目 (闽教科 〔2018〕47 号)

Group Decision Making Method Based on Evidential Reasoning Rule Under Conflicting Interval Belief Structures

Expand
  • 1. Decision Sciences Institute,Fuzhou University,Fuzhou 350116,Fujian,China; 2. Key Laboratory of Spatial Data Mining & Information Sharing of Ministry of Education,Fuzhou University,Fuzhou 350116,Fujian,China; 3. School of Architecture Engineering,Tongling University,Tongling 244061,Anhui,China; 4. Information Engineering Department,Fujian Business University,Fuzhou 350506,Fujian,China
张兴贤(1984-),男,博士生,主要从事决策理论与方法研究。E-mail:307527397@qq.com

Received date: 2019-10-31

  Revised date: 2020-01-10

  Online published: 2020-06-01

Supported by

Supported by the National Natural Science Foundation of China (61773123) and the National Social Science Foundation of China (19BGL016)

摘要

针对区间信念结构组合问题,考虑群决策环境下专家意见冲突的情形,提出一种冲突的区间信念结构下基于证据推理规则的群决策方法。首先,依据决策者 (或专家) 对备选方案的评价信息形成群体决策问题,将专家的评价信息 (观点) 作为证据,检查评价信息的有效性并做归一化处理; 其次,依据证据支持度确定专家权重向量,并运用证据推理规则融合所有评价信息; 最后,运用最小最大后悔值法选出最优方案。实例分析表明,文中所提出的方法在证据组合过程中的证据融合结果始终保持一致,组合结果合理、收敛,而且能保持证据的特异性。

本文引用格式

张兴贤 王应明 陈圣群 . 冲突的区间信念结构下基于证据推理规则的群决策方法[J]. 华南理工大学学报(自然科学版), 2020 , 48(6) : 134 -142 . DOI: 10.12141/j.issn.1000-565X.190789

Abstract

A group decision making method based on evidential reasoning rule under conflicting interval belief structures was proposed to solve the problem of interval belief structures combination,considering the conflict expert opinions in the group decision-making environment. Firstly,group decision-making problems were formed based on the evaluation information of decision makers (or experts) on alternatives. Expert evaluation information (points of view) was taken as evidence,and the validity of evaluation information was checked and normalized. Secondly,the expert weight vector was determined by the support of the evidence,and all the evaluation information was fused with the evidential reasoning rule. Finally,the minimum and maximum regret value method was used to select the optimal scheme. The case analysis shows that the proposed method has consistent evidence fusion results in the process of evidence combination,and the combination results are reasonable and convergent. In addition,the spe-cificity of the evidence can also be maintained.
文章导航

/