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

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  • Lachhwani, Kailash

Abstract

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.

Suggested Citation

  • Lachhwani, Kailash, 2015. "Modified FGP approach for multi-level multi objective linear fractional programming problems," Applied Mathematics and Computation, Elsevier, vol. 266(C), pages 1038-1049.
    • Handle: RePEc:eee:apmaco:v:266:y:2015:i:c:p:1038-1049
    DOI: 10.1016/j.amc.2015.06.027
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    References listed on IDEAS

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    1. M. S. Osman & O. E. Emam & M. A. El Sayed, 2017. "Stochastic Fuzzy Multi-level Multi-objective Fractional Programming Problem: A FGP Approach," OPSEARCH, Springer;Operational Research Society of India, vol. 54(4), pages 816-840, December.
    2. M. A. El Sayed & Ibrahim A. Baky & Pitam Singh, 2020. "A modified TOPSIS approach for solving stochastic fuzzy multi-level multi-objective fractional decision making problem," OPSEARCH, Springer;Operational Research Society of India, vol. 57(4), pages 1374-1403, December.
    3. Kailash Lachhwani, 2024. "An improved solution for fully neutrosophic multi-level linear programming problem based on Laplace transform," OPSEARCH, Springer;Operational Research Society of India, vol. 61(2), pages 867-896, June.
    4. Kailash Lachhwani, 2021. "Solving the general fully neutrosophic multi-level multiobjective linear programming problems," OPSEARCH, Springer;Operational Research Society of India, vol. 58(4), pages 1192-1216, December.

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