Group decision making method for site selection of car sharing stations in Istanbul using spherical fuzzy rough numbers

被引:4
作者
Akram, Muhammad [1 ]
Azam, Safeena [1 ]
Kahraman, Cengiz [2 ]
机构
[1] Univ Punjab, Dept Math, New Campus, Lahore 54590, Pakistan
[2] Istanbul Tech Univ, Ind Engn Dept, Istanbul, Turkiye
关键词
Spherical fuzzy rough numbers; Car sharing station; Dominance theory; Sensitivity analysis; MULTIMOORA; TRANSPORT; ENERGY; TOPSIS; SWARA; SET;
D O I
10.1016/j.asoc.2024.112607
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
One significant component of the sharing economy, which is expanding globally, is car sharing. In order to broaden their potential and marketing shares, service suppliers want to build more car sharing stations. In order to address the location selection challenge of car sharing stations, a new model is presented in this study that offers a convenient methodology for evaluating possible car sharing locations. In this paper, an extension of the Stepwise Weight Assessment Ratio Analysis (SWARA) technique using spherical fuzzy rough numbers (SFRN) is presented to compute the weights of criteria. The SWARA technique describes the proportional significance of one criterion in comparison to the preceding criterion. Additionally, extended SFRMULTIMOORA is proposed for ranking of alternatives. In MULTIMOORA, dominance theory is implemented to aggregate the utility values of three ranking techniques. In this study, spherical fuzzy rough numbers are used to tackle complex multi-criteria group decision making (MCGDM) problems. Highly complex data sets with a range of ambiguity levels can be managed using SFRNs thanks to their more dependable and adaptable data processing way. For convenience of understanding, a flowchart is presented to illustrate the SFR-SWARAMULTIMOORA approach. The suggested approach is applied in a case study of Istanbul, where the task is to select optimal new car-sharing station among four locations. After that, comparison of proposed method is made with the SFR-TOPSIS and SFR-WASPAS approaches. At the end, sensitivity analysis is carried out to confirm the precision of the calculations of suggested method.
引用
收藏
页数:21
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