Numerical Solution of Dual Fully Fuzzy Equations System Using Some Meta Heuristic Methods

Nowadays, there is more and more attention from researchers in solving various problems in the applied field of fuzzy equations, one of which is the fluid mechanics problem of reservoir piping. In this article, we investigate a solution to a dual fully fuzzy equations system involving triangular and trapezoidal fuzzy numbers using a numerical approach, especially meta-heuristic methods. We consider the equations system in crisp equations form as an optimization problem, and then its problems are solved. Here we compare the performance of four meta-heuristic methods, i.e., genetic algorithm (GA), chaos optimization algorithm (COA), particle swarm optimization (PSO), and grey wolf optimizer (GWO), to solve some cases in our problems. The results obtained show that PSO gives performance that is better than of other methods. Furthermore, the type of initial population number in GA affects how close the numerical solutions are to the exact solution.

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Publication Details

Journal
International Journal of Mathematical Engineering and Management Sciences
Published
2025-06-13
DOI
https://doi.org/10.33889/ijmems.2025.10.5.064
Citations
1
Primary Topic
Fuzzy Systems and Optimization
Type
article
Field-Weighted Citation Impact
2.63
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article

Numerical Solution of Dual Fully Fuzzy Equations System Using Some Meta Heuristic Methods

La Zakaria, Muhammad Ahsar Karim, Fatimatuzzahra Fatimatuzzahra, Aang Nuryaman et al.
1 citations
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article

Numerical Solution of Dual Fully Fuzzy Equations System Using Some Meta Heuristic Methods

La Zakaria, Muhammad Ahsar Karim, Fatimatuzzahra Fatimatuzzahra, Aang Nuryaman, Rafiq Arssy Arifa
article en
1 citations

Abstract

Nowadays, there is more and more attention from researchers in solving various problems in the applied field of fuzzy equations, one of which is the fluid mechanics problem of reservoir piping. In this article, we investigate a solution to a dual fully fuzzy equations system involving triangular and trapezoidal fuzzy numbers using a numerical approach, especially meta-heuristic methods. We consider the equations system in crisp equations form as an optimization problem, and then its problems are solved. Here we compare the performance of four meta-heuristic methods, i.e., genetic algorithm (GA), chaos optimization algorithm (COA), particle swarm optimization (PSO), and grey wolf optimizer (GWO), to solve some cases in our problems. The results obtained show that PSO gives performance that is better than of other methods. Furthermore, the type of initial population number in GA affects how close the numerical solutions are to the exact solution.

International Journal of Mathematical Engineering and Management SciencesVol. 10(5)
Lampung University (ID), Universitas Bandar Lampung (ID)
Openalex Percentile: Top 11%
Fuzzy Systems and Optimization
2.63
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