Fuzzy efficient iterative method for multi-objective linear fractional programming problems

Rubi Arya and Pitam Singh

Mathematics and Computers in Simulation (MATCOM), 2019, vol. 160, issue C, 39-54

Abstract: Various algorithms have been developed for the solution of Multi-objective linear fractional programming problems. An iterative approach is suggested by Valipour et al. (2014). Further, a fuzzy parametric iterative method is proposed by Arya and Singh (2017) and they proposed a more informative and fuzzy efficient solution set. In these two methods, the decision maker is bound to select an initial solution in the feasible region which is very difficult to search. In this article, an iterative fuzzy approach is proposed to search fuzzy efficient solution set for multi-objective linear fractional programming (MOLFP) problems. This approach is based on randomly generated fuzzy parametric preferences in the interval [0, 1] and the fuzzy efficient solution is obtained with the percentage of satisfaction for each objective. Some theoretical results are established for the validation of the proposed method. In the proposed method, Decision Maker (DM) can select the percentage of satisfaction degree for each objective function according to your own choices and fuzzy efficient solution set can be generated. The computational experiments show that the method is more informative and it performs better than the existing methods.

Keywords: Multi-objective optimization; Linear fractional programming; Multi-criteria decision making; Fuzzy optimization; Iterative methods (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:160:y:2019:i:c:p:39-54

DOI: 10.1016/j.matcom.2018.11.013

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