On FGP Approach to Multiobjective Quadratic Fractional Programming Problem

Multiobjective quadratic fractional programming models involve optimization of many conflicting objective functions in the mathematical form of quadratic fractional with subject to the constraints. In this paper, we present an alternate new procedure for solving multiobjective quadratic fractional p...

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Veröffentlicht in:International journal of applied and computational mathematics Jg. 3; H. 4; S. 3443 - 3453
1. Verfasser: Lachhwani, Kailash
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New Delhi Springer India 01.12.2017
Springer Nature B.V
Schlagworte:
Applications of Mathematics
Applied mathematics
Computational mathematics
Computational Science and Engineering
Goal programming
Mathematical and Computational Physics
Mathematical Modeling and Industrial Mathematics
Mathematical models
Mathematics
Mathematics and Statistics
Multiple objective analysis
Nuclear Energy
Operations Research/Decision Theory
Original Paper
Theoretical
Multipleobjective quadratic fractional programming
Fuzzy goal programming
Membership function
Negative deviational variable
ISSN:2349-5103, 2199-5796
Online-Zugang:Volltext
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Zusammenfassung:Multiobjective quadratic fractional programming models involve optimization of many conflicting objective functions in the mathematical form of quadratic fractional with subject to the constraints. In this paper, we present an alternate new procedure for solving multiobjective quadratic fractional programming problem (MOQFPP) based on fuzzy goal programming (FGP) approach. In the proposed alternate modified technique, separate linear membership functions for each numerator and denominator function of each objective function of MOQFPP are defined. Then achievement of the maximum value of each of fuzzy goals in terms of membership functions is formulated by minimizing the sum of the negative deviational variables. The proposed modified approach is comparatively more efficient, less computational and simpler than earlier FGP technique for MOQFPP. Comparative analysis is also carried out with the help of numerical example to demonstrate the efficiency and simplicity of proposed modified approach over earlier method.
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ISSN:2349-5103
2199-5796
DOI:10.1007/s40819-017-0307-7