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Probabilistic linguistic multiple attribute group decision making for location planning of electric vehicle charging stations based on the generalized Dice similarity measures

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Abstract

The location of the electric vehicle charging station is deemed to be a multiple attribute group decision making (MAGDM) issue involving many experts and many conflicting attributes. In practical MAGDM issues, the information of uncertain and fuzzy cognitive decision is well-depicted by linguistic term sets (LTSs). These LTSs could be simply shifted into the probabilistic linguistic sets (PLTSs). In such paper, we design some novel probabilistic linguistic weighted Dice similarity measures (PLWDSM) and the probabilistic linguistic weighted generalized Dice similarity measures (PLWGDSM). Subsequently, the PLWGDSM-based MAGDM methods are presented under PLTSs. In the end, a practical case which concerns about the location planning of electric vehicle charging stations is offered to demonstrate the proposed PLWGDSM’s applicability and advantages.

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Authors and Affiliations

  1. School of Business, Sichuan Normal University, Chengdu, 610101, People’s Republic of China

    Guiwu Wei

  2. School of Statistics, Southwestern University of Finance and Economics, Chengdu, 611130, People’s Republic of China

    Cun Wei & Jiang Wu

  3. School of Finance, Southwestern University of Finance and Economics, Chengdu, 610074, People’s Republic of China

    Yanfeng Guo

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  1. Guiwu Wei
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  2. Cun Wei
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  3. Jiang Wu
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  4. Yanfeng Guo
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Correspondence to Guiwu Wei.

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Wei, G., Wei, C., Wu, J. et al. Probabilistic linguistic multiple attribute group decision making for location planning of electric vehicle charging stations based on the generalized Dice similarity measures. Artif Intell Rev 54, 4137–4167 (2021). https://doi.org/10.1007/s10462-020-09950-2

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