A linearization based on Taylor expansion to multi-objective linear fractional program with fuzzy coefficients and fuzzy decision variables

Reaching an efficient solution for multi-objective programming problem (MOPP) is not easy and may encompass some hardships due to existing more than one objective. The aim of this research was to introduce a new efficient method to tackle fully fuzzy multi-objective linear fractional programming pro...

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主要な著者: Mojtaba Borza,, Azmin Sham Rambely,
フォーマット: 論文
言語:English
出版事項: Penerbit Universiti Kebangsaan Malaysia 2024
オンライン・アクセス:http://journalarticle.ukm.my/24658/1/SS%2022.pdf
http://journalarticle.ukm.my/24658/
https://www.ukm.my/jsm/english_journals/vol53num11_2024/contentsVol53num11_2024.html
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要約:Reaching an efficient solution for multi-objective programming problem (MOPP) is not easy and may encompass some hardships due to existing more than one objective. The aim of this research was to introduce a new efficient method to tackle fully fuzzy multi-objective linear fractional programming problem (FFMOLFPP) i.e., a multi-objective linear fractional programming problem (MOLFPP) with fuzzy coefficients and fuzzy decision variables. To construct the approach, the a – cuts of the fuzzy numbers, variable transformations, the first-order Taylor series, the membership functions, and the weighted sum method are used. In two phases, this method alters the fully fuzzy problem into linear programming problem (LPP) which its solution is at least a weakly E - efficient for the main problem. Numerical examples are compared to an existing method and the outcomes demonstrate that our proposed method is much more accurate.