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

doi:10.3969/j.issn.1001-506X.2020.11.20

Abstract

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

CLC Number:

C934

Xiwen TAO, Wenqi JIANG. Three-stage consensus improvement model under interval-valued intuitionistic multi-criteria group decision-making environment based on adjustment cost[J]. Systems Engineering and Electronics, 2020, 42(11): 2570-2580.

Figures/Tables 1

References 34

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

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