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author:

Ding, Quanyu (Ding, Quanyu.) [1] | Zhang, Cheng (Zhang, Cheng.) [2] | Wang, Ying-Ming (Wang, Ying-Ming.) [3] | Goh, Mark (Goh, Mark.) [4]

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Abstract:

The hesitant fuzzy linguistic term sets (HFLTSs) are capable of accurately capturing decision makers’ subjective characteristics, thereby resolving the issue of uncertain ambiguity in decision-making concerning existing ship water pollutant receiving facilities (SWPRF). This paper introduces an enhanced TODIM approach that incorporates optimized dominance degrees to overcome the shortcomings associated with current research assumptions regarding known weights, artificial elements, and disregard for decision makers’ psychological behavior. Firstly, we introduce a new HFLTS hesitancy degree (HFLTS-HD) and bidirectional projection model to handle the problem of unknown weights. Moreover, our proposed model incorporates attribute weights, decision maker weights, and hesitant fuzzy linguistic weighted operators. Secondly, considering the inconsistency in the cardinality of elements within the hesitant fuzzy linguistic term set, we define the hesitant fuzzy linguistic signed distance (HFLSD). Eventually, using Taizhou SWPRF and its disposal facilities as a case study, the effectiveness of the proposed scheme is demonstrated, while highlighting the superiority of the proposed method through a comparison with two existing approaches. © The Author(s) under exclusive licence to Taiwan Fuzzy Systems Association 2023.

Keyword:

Behavioral research Decision making Linguistics Ships Water pollution

Community:

  • [ 1 ] [Ding, Quanyu]School of Management and E-Business, Zhejiang Gongshang University, Zhejiang, Hangzhou; 310018, China
  • [ 2 ] [Zhang, Cheng]School of Law, Fuzhou University, Fujian, Fuzhou; 350116, China
  • [ 3 ] [Wang, Ying-Ming]Key Laboratory of Spatial Data Mining & Information Sharing of Ministry of Education, Fuzhou University, Fujian, Fuzhou; 350116, China
  • [ 4 ] [Goh, Mark]NUS Business School and The Logistics Institute–Asia Pacific, National University of Singapore, Singapore, Singapore

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Source :

International Journal of Fuzzy Systems

ISSN: 1562-2479

Year: 2024

Issue: 2

Volume: 26

Page: 613-624

3 . 6 0 0

JCR@2023

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ESI Highly Cited Papers on the List: 0 Unfold All

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30 Days PV: 0

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