The Different Approach of Solution for Multi-objective Fractional Programming Problems Under Fuzzy Environment

According to the literature, we can use several linearisation processes to develop a novel technique for solving the multi-objective linear fractional programming problem (MOLFPP) under fuzzy environment. Nevertheless, there hasn’t been any discussion of the comparative studies of solutions in the l...

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Veröffentlicht in:International journal of applied and computational mathematics Jg. 10; H. 6; S. 176
Hauptverfasser: Sahoo, Deepanjali, Tripathy, Arun Kumar, Pati, Jitendra Kumar, Parida, Prashanta Kumar
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New Delhi Springer India 01.12.2024
Springer Nature B.V
Schlagworte:
Algorithms
Applications of Mathematics
Comparative studies
Computational Science and Engineering
Decision making
Fuzzy sets
Hyperbolic functions
Linear programming
Linearization
Mathematical and Computational Physics
Mathematical Modeling and Industrial Mathematics
Mathematical programming
Mathematics
Mathematics and Statistics
Nuclear Energy
Operations Research/Decision Theory
Optimization
Original Paper
Ratios
Software
Theoretical
90C32
Decision maker
Linear membership function
Hyperbolic membership function
Exponential membership function
90C29
Multi-objective linear fractional programming problem
90C70
ISSN:2349-5103, 2199-5796
Online-Zugang:Volltext
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Zusammenfassung:According to the literature, we can use several linearisation processes to develop a novel technique for solving the multi-objective linear fractional programming problem (MOLFPP) under fuzzy environment. Nevertheless, there hasn’t been any discussion of the comparative studies of solutions in the literature. This article discusses various approaches for applying linearisation techniques to convert multi-objective linear fractional programming problem (MOLFPP) into multi-objective linear programming problem (MOLPP). A comparative analysis is then conducted. In order to showcase our work, we employ several strategies for linearisation, and we explore membership functions such as linear membership function, hyperbolic membership function and exponential membership function.
Bibliographie:ObjectType-Article-1
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ISSN:2349-5103
2199-5796
DOI:10.1007/s40819-024-01793-7