Performance Analysis of Fully Intuitionistic Fuzzy Multi-Objective Multi-Item Solid Fractional Transportation Model

被引:2
|
作者
Almotairi, Sultan [1 ,2 ]
Badr, Elsayed [3 ,4 ]
Elsisy, M. A. [5 ]
Farahat, F. A. [6 ]
El Sayed, M. A. [5 ,7 ]
机构
[1] Majmaah Univ, Fac Coll Comp & Informat Sci, Dept Comp Sci, Majmaah 11952, Saudi Arabia
[2] Islamic Univ Madinah, Fac Comp & Informat Syst, Dept Comp Sci, Medinah 42351, Saudi Arabia
[3] Benha Univ, Fac Comp & Artificial Intelligence, Sci Comp Dept, Banha 13511, Egypt
[4] Egyptian Sch Data Sci ESDS, Banha, Egypt
[5] Benha Univ, Fac Engn, Dept Basic Engn Sci, El Qalyoubia 13511, Egypt
[6] Higher Technol Inst, Cairo 10116, Egypt
[7] BADR Univ Cairo BUC, Fac Engn, Basic Sci Dept, Cairo 11829, Egypt
关键词
intuitionistic fuzzy set; multi-objective optimization; accuracy function fractional transportation problem; PROGRAMMING TECHNIQUE; COST;
D O I
10.3390/fractalfract8070404
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
An investigation is conducted in this paper into a performance analysis of fully intuitionistic fuzzy multi-objective multi-item solid fractional transport model (FIF-MMSFTM). It is to be anticipated that the parameters of the conveyance model will be imprecise by virtue of numerous uncontrollable factors. The model under consideration incorporates intuitionistic fuzzy (IF) quantities of shipments, costs and profit coefficients, supplies, demands, and transport. The FIF-MMSFTM that has been devised is transformed into a linear form through a series of operations. The accuracy function and ordering relations of IF sets are then used to reduce the linearized model to a concise multi-objective multi-item solid transportation model (MMSTM). Furthermore, an examination is conducted on several theorems that illustrate the correlation between the FIF-MMSFTM and its corresponding crisp model, which is founded upon linear, hyperbolic, and parabolic membership functions. A numerical example was furnished to showcase the efficacy and feasibility of the suggested methodology. The numerical data acquired indicates that the linear, hyperbolic, and parabolic models require fewer computational resources to achieve the optimal solution. The parabolic model has the greatest number of iterations, in contrast to the hyperbolic model which has the fewest. Additionally, the elapsed run time for the three models is a negligible amount of time: 0.2, 0.15, and 1.37 s, respectively. In conclusion, suggestions for future research are provided.
引用
收藏
页数:29
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