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A Multi-Attribute Group Decision-Making Method Based on Linguistic Intuitionistic Fuzzy Numbers and Dempster–Shafer Evidence Theory

Author

Listed:
  • Peide Liu

    (School of Management Science and Engineering, Shandong University of Finance and Economics, Jinan, Shandong, China)

  • Xiaoxiao Liu

    (School of Management Science and Engineering, Shandong University of Finance and Economics, Jinan, Shandong, China)

  • Guiying Ma

    (#x2020;Price Monitoring Center in Shandong Province, Jinan, Shandong, China)

  • Zhaolong Liang

    (#x2020;Price Monitoring Center in Shandong Province, Jinan, Shandong, China)

  • Changhai Wang

    (#x2020;Price Monitoring Center in Shandong Province, Jinan, Shandong, China)

  • Fawaz E. Alsaadi

    (#x2021;Department of Information Technology, Faculty of Computing and IT, King Abdulaziz University, Jeddah, Saudi Arabia)

Abstract

In this paper, we propose a multi-attribute group decision-making (MAGDM) method based on Dempster–Shafer Evidence Theory (DST) and linguistic intuitionistic fuzzy numbers (LIFNs), in which both the expert weights and attribute weights are unknown. Firstly, we represent LIFNs as basic probability assignments (BPAs) by DST based on linguistic scale function (LSF), and a linear programming model is proposed to combine the objective weights and subjective weights of attributes to obtain the combined weights. At the same time, the experts’ weights are obtained through Jousselme distance. Secondly, we use the weights to correct the evidence, and the comprehensive evaluation value of each alternative is calculated by the combination rule of evidence. Further, a new MAGDM approach with DST and LIFNs is presented. Finally, we give an example to explain the proposed method and compare it with other methods to show the feasibility and superiority.

Suggested Citation

  • Peide Liu & Xiaoxiao Liu & Guiying Ma & Zhaolong Liang & Changhai Wang & Fawaz E. Alsaadi, 2020. "A Multi-Attribute Group Decision-Making Method Based on Linguistic Intuitionistic Fuzzy Numbers and Dempster–Shafer Evidence Theory," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 19(02), pages 499-524, April.
    • Handle: RePEc:wsi:ijitdm:v:19:y:2020:i:02:n:s0219622020500042
    DOI: 10.1142/S0219622020500042
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    References listed on IDEAS

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    1. Wen Jiang & Boya Wei, 2018. "Intuitionistic fuzzy evidential power aggregation operator and its application in multiple criteria decision-making," International Journal of Systems Science, Taylor & Francis Journals, vol. 49(3), pages 582-594, February.
    2. Peide Liu & Peng Wang, 2017. "Some Improved Linguistic Intuitionistic Fuzzy Aggregation Operators and Their Applications to Multiple-Attribute Decision Making," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 16(03), pages 817-850, May.
    3. Zhang, Huanhuan & Kou, Gang & Peng, Yi, 2019. "Soft consensus cost models for group decision making and economic interpretations," European Journal of Operational Research, Elsevier, vol. 277(3), pages 964-980.
    4. Mehran Khalaj & Reza Tavakkoli-Moghaddam & Fereshteh Khalaj & Ali Siadat, 2020. "New definition of the cross entropy based on the Dempster-Shafer theory and its application in a decision-making process," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 49(4), pages 909-923, February.
    5. R. Krishankumar & K. S. Ravichandran & J. Premaladha & Samarjit Kar & Edmundas Kazimieras Zavadskas & Jurgita Antucheviciene, 2018. "A Decision Framework under a Linguistic Hesitant Fuzzy Set for Solving Multi-Criteria Group Decision Making Problems," Sustainability, MDPI, vol. 10(8), pages 1-21, July.
    6. Guangxu Li & Gang Kou & Changsheng Lin & Liang Xu & Yi Liao, 2015. "Multi-attribute decision making with generalized fuzzy numbers," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 66(11), pages 1793-1803, November.
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