Missing values estimation and consensus building for incomplete hesitant fuzzy preference relations with multiplicative consistency
- DOI
- 10.2991/ijcis.11.1.9How to use a DOI?
- Keywords
- Hesitant fuzzy preference relation; Incomplete hesitant fuzzy preference relation; Multiplicative consistency; Group decision making; Consensus
- Abstract
This paper proposes a decision support process for incomplete hesitant fuzzy preference relations (HFPRs). First, we present a revised definition of HFPRs, in which the values are not ordered for the hesitant fuzzy element. Second, we propose a method to normalize the HFPRs and estimate the missing elements in incomplete HFPRs based on multiplicative consistency. Based on this, a consensus model with incomplete HFPR is developed. A feedback mechanism is proposed to obtain a best choice with desired consensus level. Multiplicative consistency induced ordered weighted averaging (MC-IOWA) operator is used to aggregate the individual HFPRs into a collective one. A score HFPR is proposed for collective HFPR, and then the hesitant quantifier-guided non-dominance degrees (HQGNDD) of alternatives by using an OWA operator are obtained to rank the alternatives. Finally, a case study for evaluate the qualification of supply chain enterprises is provided to illustrate its application.
- Copyright
- © 2018, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).
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TY - JOUR AU - Yejun Xu AU - Caiyun Li AU - Xiaowei Wen PY - 2018 DA - 2018/01/01 TI - Missing values estimation and consensus building for incomplete hesitant fuzzy preference relations with multiplicative consistency JO - International Journal of Computational Intelligence Systems SP - 101 EP - 119 VL - 11 IS - 1 SN - 1875-6883 UR - https://doi.org/10.2991/ijcis.11.1.9 DO - 10.2991/ijcis.11.1.9 ID - Xu2018 ER -