Solving Multi-level Multi-objective Fractional Programming Problems with Fuzzy Demands via FGP Approach

This paper presents a fuzzy goal programming approach for solving multi-level multi-objective fractional programming problem with fuzzy demands. It makes an extension work of Pal et al. (Fuzzy Sets Syst 139(2):395–405, 2003 ). Firstly, the concept of α -cut is applied to transform the fuzzy mathemat...

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Veröffentlicht in:International journal of applied and computational mathematics Jg. 4; H. 1; S. 1 - 24
Hauptverfasser: Osman, M. S., Emam, O. E., El Sayed, M. A.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New Delhi Springer India 01.02.2018
Springer Nature B.V
Schlagworte:
Applications of Mathematics
Applied mathematics
Computational mathematics
Computational Science and Engineering
Fuzzy sets
Goal programming
Mathematical and Computational Physics
Mathematical Modeling and Industrial Mathematics
Mathematical models
Mathematical programming
Mathematics
Mathematics and Statistics
Multiple objective analysis
Nuclear Energy
Operations Research/Decision Theory
Original Paper
Theoretical
Multi-level programming
Fuzzy sets
90C32
90C99
Fuzzy goal programming
90C29
Multi-objective programming
Fractional programming
90C70
ISSN:2349-5103, 2199-5796
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Zusammenfassung:This paper presents a fuzzy goal programming approach for solving multi-level multi-objective fractional programming problem with fuzzy demands. It makes an extension work of Pal et al. (Fuzzy Sets Syst 139(2):395–405, 2003 ). Firstly, the concept of α -cut is applied to transform the fuzzy mathematical problem into a common deterministic one. Then, the membership functions for the defined fuzzy goals are developed. Also, in the proposed approach, linearization of membership goals of the objective functions is presented. Secondly, the highest degree of each of these membership goals is achieved by minimizing the sum of the negative deviational variables. Moreover, the final model is simplified by eliminating solution preferences by the decision makers at each level, thereby avoiding decision deadlock situations. Finally, an illustrative numerical examples and comparisons with the existing methods are used to demonstrate the applicability and performance of the proposed approach.
Bibliographie:ObjectType-Article-1
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ISSN:2349-5103
2199-5796
DOI:10.1007/s40819-017-0467-5