Novel Cross-Entropy Based on Multi-attribute Group Decision-Making with Unknown Experts' Weights Under Interval-Valued Intuitionistic Fuzzy Environment
- DOI
- 10.2991/ijcis.d.200817.001How to use a DOI?
- Keywords
- Interval-valued intuitionistic fuzzy set; Experts' weights; Cross-entropy; Multi-attribute group decision-making
- Abstract
This paper studies the multi-attribute group decision-making problems with unknown experts' weights under interval-valued intuitionistic fuzzy environment. First, in order to provide more flexibilities for decision-makers in actual decision-making problems, a novel cross-entropy measure with parameter of interval-valued intuitionistic fuzzy set (IVIFS) based on J-divergence is proposed. The novel cross-entropy measure can obtain more flexible and practical optimal ranking results by adjusting the parameter. Then, by using the designed cross-entropy measure, two models are established to obtain experts' weights, which consider the influence of experts' experience and professional knowledge on experts' weights. Finally, two examples are provided to illustrate the effectiveness and applicability of optimizing the group decision-making approach.
- Copyright
- © 2020 The Authors. Published by Atlantis Press B.V.
- Open Access
- This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).
Download article (PDF)
View full text (HTML)
Cite this article
TY - JOUR AU - Yonghong Li AU - Yali Cheng AU - Qiong Mou AU - Sidong Xian PY - 2020 DA - 2020/08/29 TI - Novel Cross-Entropy Based on Multi-attribute Group Decision-Making with Unknown Experts' Weights Under Interval-Valued Intuitionistic Fuzzy Environment JO - International Journal of Computational Intelligence Systems SP - 1295 EP - 1304 VL - 13 IS - 1 SN - 1875-6883 UR - https://doi.org/10.2991/ijcis.d.200817.001 DO - 10.2991/ijcis.d.200817.001 ID - Li2020 ER -