TY - JOUR
T1 - Study of site selection of electric vehicle charging station based on extended GRP method under picture fuzzy environment
AU - Ju, Yanbing
AU - Ju, D.
AU - Santibanez Gonzalez, Ernesto D.R.
AU - Giannakis, Mihalis
AU - Wang, A.
N1 - Publisher Copyright:
© 2018 Elsevier Ltd
PY - 2019/9
Y1 - 2019/9
N2 - Electric vehicle charging station (EVCS) site selection problem plays an important role in promoting electric vehicle industry development. The purpose of EVCS site selection is to find optimal location considering some conflicting criteria. To handle the uncertainty of information in EVCS site selection problem, the picture fuzzy set (PFS) is a good choice, which is characterized by three functions: the degree of positive membership, the degree of neutral membership and the degree of negative membership. In this paper, an effective comprehensive framework is proposed to evaluate and select the optimal EVCS site under picture fuzzy environment. Firstly, from the perspective of sustainability, some main criteria and corresponding sub-criteria are determined by reference to the existing literature and experiences of experts. Secondly, some operational laws of picture fuzzy numbers (PFNs) are defined and the picture fuzzy weighted interaction geometric (PFWIG) operator is developed. Thirdly, fuzzy analytic hierarchy process (FAHP) technique is utilized to determine the weights of criteria and the local weights of corresponding sub-criteria before comprehensive picture fuzzy decision matrix is further constructed based on the developed PFWIG operator. Afterwards, the traditional grey relational projection (GRP) method is extended to calculate the relative grey relational projection of each EVCS site. Thus, all EVCS sites are ranked and the most desirable one(s) can be selected. Finally, an empirical example about EVCS site selection in Beijing is given to illustrate the application of the proposed framework. The results indicate that the proposed framework is useful for identifying suitable EVCS site among the potential charging stations.
AB - Electric vehicle charging station (EVCS) site selection problem plays an important role in promoting electric vehicle industry development. The purpose of EVCS site selection is to find optimal location considering some conflicting criteria. To handle the uncertainty of information in EVCS site selection problem, the picture fuzzy set (PFS) is a good choice, which is characterized by three functions: the degree of positive membership, the degree of neutral membership and the degree of negative membership. In this paper, an effective comprehensive framework is proposed to evaluate and select the optimal EVCS site under picture fuzzy environment. Firstly, from the perspective of sustainability, some main criteria and corresponding sub-criteria are determined by reference to the existing literature and experiences of experts. Secondly, some operational laws of picture fuzzy numbers (PFNs) are defined and the picture fuzzy weighted interaction geometric (PFWIG) operator is developed. Thirdly, fuzzy analytic hierarchy process (FAHP) technique is utilized to determine the weights of criteria and the local weights of corresponding sub-criteria before comprehensive picture fuzzy decision matrix is further constructed based on the developed PFWIG operator. Afterwards, the traditional grey relational projection (GRP) method is extended to calculate the relative grey relational projection of each EVCS site. Thus, all EVCS sites are ranked and the most desirable one(s) can be selected. Finally, an empirical example about EVCS site selection in Beijing is given to illustrate the application of the proposed framework. The results indicate that the proposed framework is useful for identifying suitable EVCS site among the potential charging stations.
KW - Electric vehicle charging station (EVCS)
KW - Fuzzy analytic hierarchy process (FAHP)
KW - Grey relational projection (GRP) method
KW - Picture fuzzy set (PFS)
KW - Picture fuzzy weighted interaction geometric (PFWIG) operator
KW - Site selection
UR - http://www.scopus.com/inward/record.url?scp=85050998896&partnerID=8YFLogxK
U2 - 10.1016/j.cie.2018.07.048
DO - 10.1016/j.cie.2018.07.048
M3 - Article
AN - SCOPUS:85050998896
SN - 0360-8352
VL - 135
SP - 1271
EP - 1285
JO - Computers and Industrial Engineering
JF - Computers and Industrial Engineering
ER -