Modified FGP approach for multi-level multi objective linear fractional programming problems

In this paper, we present a new modified method for solving multi-level multi objective linear fractional programming problems (ML-MOLFPPs) based on fuzzy goal programming (FGP) approach with some modifications in the algorithm suggested by Baky (2010) [18] which dealt with multi-level multi objecti...

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Vydáno v:Applied mathematics and computation Ročník 266; s. 1038 - 1049
Hlavní autor: Lachhwani, Kailash
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier Inc 01.09.2015
Témata:
Compromise optimal solution
Fuzzy goal programming
Membership function
Multi-level multi objective linear fractional programming problem
Compromise optimal solution
Fuzzy goal programming
Membership function
Multi-level multi objective linear fractional programming problem
ISSN:0096-3003, 1873-5649
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Shrnutí:In this paper, we present a new modified method for solving multi-level multi objective linear fractional programming problems (ML-MOLFPPs) based on fuzzy goal programming (FGP) approach with some modifications in the algorithm suggested by Baky (2010) [18] which dealt with multi-level multi objective linear programming problem (ML-MOLPP). In proposed modified approach, numerator and denominator function of each objective at each level are individually transformed into fuzzy goals and their aspiration levels are determined using individual best solutions. Different linear membership functions are defined for numerator and denominator function of each objective function. Then highest degree of each of these membership goals is achieved by minimising the sum of negative deviational variables. The proposed algorithm simplifies the ML-MOLFPP by eliminating solution preferences by the decision makers at each level, thereby avoiding difficulties associate with multi-level programming problems and decision deadlock situations. The aim of this paper is to present simple and efficient technique to obtain compromise optimal solution of ML-MOLFP problems. Numerical examples are illustrated in order to support the proposed modified FGP technique.
ISSN:0096-3003
1873-5649
DOI:10.1016/j.amc.2015.06.027