共 55 条
An efficient spherical fuzzy MEREC-CoCoSo approach based on novel score function and aggregation operators for group decision making
被引:15
作者:
Wan, Guorou
[1
]
Rong, Yuan
[2
]
Garg, Harish
[3
,4
,5
,6
]
机构:
[1] Sichuan Coll Architectural Technol, Dept Basic Educ, Deyang 618000, Peoples R China
[2] Shanghai Univ, Sch Management, Shanghai 200444, Peoples R China
[3] Deemed Univ, Thapar Inst Engn & Technol, Sch Math, Patiala 147004, Punjab, India
[4] Graphics Era Deemed Univ, Dept Math, Dehra Dun 248002, Uttarakhand, India
[5] Appl Sci Private Univ, Appl Sci Res Ctr, Amman 11931, Jordan
[6] Islamic Univ, Coll Tech Engn, Najaf, Iraq
关键词:
Spherical fuzzy set;
MCGDM;
Information fusion;
MEREC;
CoCoSo;
T-CONORM;
D O I:
10.1007/s41066-023-00381-2
中图分类号:
TP18 [人工智能理论];
学科分类号:
081104 ;
0812 ;
0835 ;
1405 ;
摘要:
The major objective of the current investigation is to build an integrated multiple criteria group decision-making (MCGDM) methodology based on combined compromise solution (CoCoSo) and spherical fuzzy set for determining the optimal solar power station. To begin with, an innovative spherical fuzzy score function is brought forward to strengthen the efficiency of the comparison for spherical fuzzy number (SFN). Secondly, several newly operational laws for SFN are defined and some novel aggregation operation based on them are propounded. The corresponding excellent properties of the novel operators are also explored at length. Further, the spherical fuzzy method on the removal effects of criteria (MEREC) technique is presented by the proposed score function to work out the importance of the criteria. Lastly, an MCGDM approach is propounded based on improved spherical fuzzy CoCoSo to obtain the ranking of the solar power station locations. The feasibility and practicability of the proposed SF-MEREC-CoCoSo method are investigated through the comparison study with the extant methods. The sensibility analysis is also executed to discuss the robustness and stability of the propounded methodology.
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页码:1481 / 1503
页数:23
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