系统工程与电子技术 ›› 2020, Vol. 42 ›› Issue (11): 2570-2580.doi: 10.3969/j.issn.1001-506X.2020.11.20

• 系统工程 • 上一篇    下一篇

基于调整成本的三阶段区间直觉模糊型多准则群体共识改进模型

陶希闻1(), 江文奇1,2()   

  1. 1. 南京理工大学经济管理学院, 江苏 南京 210094
    2. 江苏产业集群决策咨询研究基地, 江苏 南京 210094
  • 收稿日期:2020-01-13 出版日期:2020-11-01 发布日期:2020-11-05
  • 作者简介:陶希闻(1995-),男,博士研究生,主要研究方向为评价与决策。E-mail:1206868096@qq.com|江文奇(1976-),男,教授,博士研究生导师,博士,主要研究方向为评价与决策。E-mail:wq_jiang@126.com
  • 基金资助:
    国家自然科学基金(71971117);教育部人文社科基金(17YJA630035);南京理工大学自主科研培育项目(30916011331);江苏省研究生科研与实践创新计划项目(KYCX19_0230)

Three-stage consensus improvement model under interval-valued intuitionistic multi-criteria group decision-making environment based on adjustment cost

Xiwen TAO1(), Wenqi JIANG1,2()   

  1. 1. School of Economics and Management, Nanjing University of Science and Technology, Nanjing 210094, China
    2. Jiangsu Industrial Cluster Decision Consulting Research Base, Nanjing 210094, China
  • Received:2020-01-13 Online:2020-11-01 Published:2020-11-05

摘要:

群体共识度是实现高效群决策的重要指标,较高群体共识的实现是一个多阶段多约束的动态决策过程。本文提出了高水平群体共识的构建包含群体信息集结、调整元素识别和元素调整步长设计3个阶段,并以相似度作为群体共识度刻画指标贯穿于3个阶段。首先,以相似度为诱导变量进行区间直觉模糊型群体信息集结;其次,基于统计假设检验思想和相似度近似正态分布的构想,识别需要调整的元素集合(决策方案在特定准则下的评估值和决策者);再次,以最小化调整成本为决策目标,以共识度阈值、个体相似度保序、最小调整量、区间直觉模糊评价值特征为约束条件,构建共识度改进优化决策模型;最后,通过比较分析凸显本文算法的可行性和优越性。

关键词: 群体共识, 区间直觉模糊集, 相似度, 调整成本

Abstract:

Group consensus degree is a significant indicator of an effective group decision making process, and group consensus reaching is a multi-stage and multi-constrains dynamic process. This paper considers that this process consists of group assessments aggregation, adjusted elements identification and adjustment step size determination, where similarity measurement is used to describe group consensus degree. First of all, similarity measurement is used as the order induced variable to aggregate individual interval-valued intuitionistic fuzzy information. Secondly, based on statistical inference and the distribution of similarity, the elements which need adjustment (the alternatives with specific attributes and decision makers) are identified. And then, driven by minimizing adjustment cost, construct a non-linear programming model to improve group consensus, with constrains of consensus threshold, individual similarity order preservation, minimal adjustment step size and characteristics of interval-valued intuitionistic fuzzy information. Finally, a comparison with the existing approach is carried out to show the effectiveness and efficiency of the proposed method.

Key words: group consensus, interval-valued intuitionistic fuzzy set, similarity measurement, adjustment cost

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