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A multihesitant fuzzy linguistic multicriteria decision-making approach for logistics outsourcing with incomplete weight information

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成果类型:
期刊论文
作者:
Wang, Jing*;Wang, Jian-qiang;Tian, Zhang-peng;Zhao, Dong-yan
通讯作者:
Wang, Jing
作者机构:
[Wang, Jing; Wang, Jian-qiang; Tian, Zhang-peng] Cent S Univ, Sch Business, Management Sci & Informat Management Dept, Changsha 410083, Peoples R China
[Wang, Jing; Zhao, Dong-yan] Cent South Univ Forestry & Technol, Business & Econ Dept, Int Coll, Changsha 410004, Hunan, Peoples R China
通讯机构:
[Wang, Jing] C
Cent S Univ, Sch Business, Management Sci & Informat Management Dept, Changsha 410083, Peoples R China. Cent South Univ Forestry & Technol, Business & Econ Dept, Int Coll, Changsha 410004, Hunan, Peoples R China.
语种:
英文
关键词:
Decision making;Outsourcing;Average operator;Fuzzy linguistics;Heronian means;Incomplete weight informations;Logistics outsourcing;Logistics service provider;Multi criteria decision making;Qualitative criteria;Linguistics
期刊:
International Transactions in Operational Research
ISSN:
0969-6016
年:
2018
卷:
25
期:
3
页码:
831-856
基金类别:
The authors would like to thank the editors and the anonymous referees for their valuable and constructive comments and suggestions that greatly helped to improve this paper. This work was supported by the National Natural Science Foundation of China (nos. 71571193, 71501192, and 71401185) and Hunan Provincial Philosophy and Social Science Foundation of China (no. 16YBA378).
机构署名:
本校为通讯机构
院系归属:
国际学院
摘要:
In selecting logistics service providers, the evaluation criteria can be easily prioritized and possibly interrelated with each other, and the assessment of alternatives under qualitative criteria is usually accomplished by more than one decision maker. A novel multicriteria decision-making approach with multihesitant fuzzy linguistic term elements (MHFLTEs) based on the Heronian mean (HM) and prioritized average operators can effectively deal with the problems inherent in such a scenario. Multihesitant fuzzy linguistic term sets (MHFLTSs) were...

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