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

2021 ◽  
Author(s):  
Guiwu Wei ◽  
Cun Wei ◽  
Jiang Wu ◽  
Yanfeng Guo
Keyword(s):  
Decision Making ◽  
Electric Vehicle ◽  
Group Decision Making ◽  
Group Decision ◽  
Similarity Measures ◽  
Location Planning ◽  
Electric Vehicle Charging ◽  
Multiple Attribute ◽  
Vehicle Charging ◽  
Charging Stations

scholarly journals Optimal Siting of Electric Vehicle Charging Stations Using Pythagorean Fuzzy VIKOR Approach

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Feng-Bao Cui ◽  
Xiao-Yue You ◽  
Hua Shi ◽  
Hu-Chen Liu
Keyword(s):  
Decision Making ◽  
Electric Vehicle ◽  
Site Selection ◽  
Multicriteria Decision Making ◽  
Pythagorean Fuzzy Set ◽  
Fuzzy Vikor ◽  
Electric Vehicle Charging ◽  
Vehicle Charging ◽  
Alternative Sites ◽  
Charging Stations

Site selection for electric vehicle charging stations (EVCSs) is the process of determining the most suitable location among alternatives for the construction of charging facilities for electric vehicles. It can be regarded as a complex multicriteria decision-making (MCDM) problem requiring consideration of multiple conflicting criteria. In the real world, it is often hard or impossible for decision makers to estimate their preferences with exact numerical values. Therefore, Pythagorean fuzzy set theory has been frequently used to handle imprecise data and vague expressions in practical decision-making problems. In this paper, a Pythagorean fuzzy VIKOR (PF-VIKOR) approach is developed for solving the EVCS site selection problems, in which the evaluations of alternatives are given as linguistic terms characterized by Pythagorean fuzzy values (PFVs). Particularly, the generalized Pythagorean fuzzy ordered weighted standardized distance (GPFOWSD) operator is proposed to calculate the utility and regret measures for ranking alternative sites. Finally, a practical example in Shanghai, China, is included to demonstrate the proposed EVCS sitting model, and the advantages are highlighted by comparing the results with other relevant methods.

scholarly journals Similarity Measures of Linguistic Cubic Hesitant Variables for Multiple Attribute Group Decision-Making

Information ◽  
2019 ◽  
Vol 10 (5) ◽  
pp. 168 ◽  
Author(s):  
Xueping Lu ◽  
Jun Ye
Keyword(s):  
Decision Making ◽  
Similarity Measure ◽  
Group Decision Making ◽  
Group Decision ◽  
Similarity Measures ◽  
Weight Changes ◽  
Hybrid Form ◽  
Included Angle ◽  
Multiple Attribute ◽  
Language Variables

A linguistic cubic hesitant variable (LCHV) is a hybrid form of linguistic values in group decision-making environments. It is composed of an interval language variable and multiple single-valued language variables given by different decision-makers (DMs). Due to the uncertainty and hesitation of DMs, the numbers of language variables in different LCHVs are unequal. Thus, the least common multiple number (LCMN) extension method was adopted. Based on the included angle and distance of two LCHVs, we presented two cosine similarity measures and developed a multiple attribute group decision-making (MAGDM) approach. An example of engineer selection was used to implement the proposed LCHV MAGDM method and demonstrate the simplicity and feasibility of the proposed method. The sensitivity analysis of weight changes for the two measures showed that the similarity measure based on distance was more stable than the similarity measure based on included angle in this application.

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