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Article type: Research Article
Authors: Borza, Mojtaba | Rambely, Azmin Sham; *
Affiliations: Department of Mathematical Sciences, Faculty of Science & Technology, UKM Bangi, Selangor, Malaysia
Correspondence: [*] Corresponding author. Azmin Sham Rambely, Department of Mathematical Sciences, Faculty of Science & Technology, UKM Bangi, Selangor, Malaysia. E-mail: asr@ukm.edu.my.
Abstract: Finding efficient solutions for the multi-objective linear fractional programming problem (MOLFPP) is a challenging issue in optimization because more than one target has to be taken into account. For the problem, we face the concept of efficient solutions which is an infinite set especially when the objectives are in conflict. Since a classical method generally comes out with only one efficient solution, thus introducing new efficient approaches is helpful and beneficial for the decision makers to make their decisions according to more possibilities. In this paper, we aim to consider the MOLFPP with fuzzy coefficients (FMOLFPP) where the concept of α - cuts is utilized so as to transform the fuzzy numbers into closed intervals and rank the fuzzy numbers as well. Consequently, the fuzzy problem is changed into an interval valued multi-objective linear fractional programming problem (IV-MOLFPP). Subsequently, the IV-MOLFPP is further changed into linear programming problems (LPPs) using a parametric approach, weighted sum and max-min methods. It is demonstrated that the solution obtained is at least a weakly ɛ - efficient solution, where the value of ɛ helps a decision maker (DM) to make his decision appropriately i.e. DMs chose more likely the solutions with the lowest value of ɛ. Numerical examples are solved to illustrate the method and comparison are made to show the accuracy, and the reliability of the proposed solutions.
Keywords: Efficient solution, weighted sum approach, parametric approach, fuzzy numbers, interval arithmetic
DOI: 10.3233/JIFS-212403
Journal: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 1, pp. 721-734, 2022
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