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Hesitant fuzzy information measures and their applications in multi-criteria decision making

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  • Junhua Hu
  • Xiaolong Zhang
  • Xiaohong Chen
  • Yongmei Liu

Abstract

Hesitant fuzzy set (HFS) is a powerful decision tool to express uncertain information more flexibly and comprehensively. The aim of this paper is to propose more reasonable information measures for HFSs in comparison with the existing ones. First, a series of distance measures is suggested for hesitant fuzzy element and hesitant fuzzy sets. These measures are directly calculated from hesitant fuzzy elements without judging the decision-makers’ risk preference and adding any values into the hesitant fuzzy element with the smaller number of elements. Then, some similarity and entropy measures are proposed based on the transforming relationship among the information measures. Additionally, based on the proposed information measures, a TOPSIS method for hesitant fuzzy information is provided. Finally, some numerical examples are used in order to illustrate the proposed decision method and a comparative analysis is made to demonstrate that the suggested measures are more objective and feasible in certain cases.

Suggested Citation

  • Junhua Hu & Xiaolong Zhang & Xiaohong Chen & Yongmei Liu, 2016. "Hesitant fuzzy information measures and their applications in multi-criteria decision making," International Journal of Systems Science, Taylor & Francis Journals, vol. 47(1), pages 62-76, January.
    • Handle: RePEc:taf:tsysxx:v:47:y:2016:i:1:p:62-76
    DOI: 10.1080/00207721.2015.1036476
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    References listed on IDEAS

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    1. Ye, Jun, 2010. "Fuzzy decision-making method based on the weighted correlation coefficient under intuitionistic fuzzy environment," European Journal of Operational Research, Elsevier, vol. 205(1), pages 202-204, August.
    2. Mohit Kumar & Shiv Prasad Yadav & Surendra Kumar, 2013. "Fuzzy system reliability evaluation using time-dependent intuitionistic fuzzy set," International Journal of Systems Science, Taylor & Francis Journals, vol. 44(1), pages 50-66.
    3. Editors, 2014. "International Journal of Systems Science," International Journal of Systems Science, Taylor & Francis Journals, vol. 45(12), pages 1-1, December.
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    Cited by:

    1. Arunodaya Raj Mishra & Pratibha Rani & Raghunathan Krishankumar & Edmundas Kazimieras Zavadskas & Fausto Cavallaro & Kattur S. Ravichandran, 2021. "A Hesitant Fuzzy Combined Compromise Solution Framework-Based on Discrimination Measure for Ranking Sustainable Third-Party Reverse Logistic Providers," Sustainability, MDPI, vol. 13(4), pages 1-24, February.
    2. Palash Dutta & Rupjit Saikia, 2020. "A Decision-making Approach for Choosing a Reliable Product under the Hesitant Fuzzy Environment via a Novel Distance Measure," Vikalpa: The Journal for Decision Makers, , vol. 45(3), pages 147-159, September.
    3. Juan-Juan Peng & Jian-Qiang Wang & Xiao-Hui Wu, 2016. "Novel Multi-criteria Decision-making Approaches Based on Hesitant Fuzzy Sets and Prospect Theory," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 15(03), pages 621-643, May.

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