Comparison of Genetic Algorithm and Particle Swarm Optimization in Determining the Solution of Nonlinear System of Equations
DOI:
10.33395/sinkron.v8i3.13785Keywords:
Genetic Algorithm, Particle Swarm Optimization, optimization methods, nonlinear equation systemsAbstract
Nonlinear systems of equations often appear in various fields of science and engineering, but their analytical solutions are difficult to find, so numerical methods are needed to solve them. Optimization algorithms are very effective in finding solutions to nonlinear systems of equations especially when traditional analytical and numerical methods are difficult to apply. Two popular optimization methods used for this purpose are Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). This study aims to compare the effectiveness of GA and PSO in finding solutions to nonlinear systems of equations. The criteria used for comparison include accuracy and speed of convergence. This research uses several examples of nonsmooth nonlinear systems of equations for experimentation and comparison. The results provide insight into when and how to effectively use these two algorithms to solve nonlinear systems of equations as well as their potential combinations
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Abiodun M., I., Olawale N., L., & Adebowale P., A. (2011). The Effectiveness of Genetic Algorithm in Solving Simultaneous Equations. International Journal of Computer Applications, 14(8), 38–41. https://doi.org/10.5120/1900-2534
Caesar, C. A., Hanum, L., & Cholissodin, I. (2016). Perbandingan Metode ANN-PSO Dan ANN-GA Dalam Pemodelan Komposisi Pakan Kambing Peranakan Etawa (PE) Untuk Optimasi Kandungan Gizi. Jurnal Teknologi Informasi Dan Ilmu Komputer, 3(3), 216. https://doi.org/10.25126/jtiik.201633200
Chu, S. C., & Tsai, P. W. (2007). Computational intelligence based on the behavior of cats. International Journal of Innovative Computing, Information and Control, 3(1), 163–173.
Krzyworzcka, S. (1996). Extension of the Lanczos and CGS methods to systems of nonlinear equations. Journal of Computational and Applied Mathematics, 69(1), 181–190. https://doi.org/10.1016/0377-0427(95)00032-1
Luo, Y. Z., Tang, G. J., & Zhou, L. N. (2008). Hybrid approach for solving systems of nonlinear equations using chaos optimization and quasi-Newton method. Applied Soft Computing Journal, 8(2), 1068–1073. https://doi.org/10.1016/j.asoc.2007.05.013
Sunandar, E., & Indrianto, I. (2020). Perbandingan Metode Newton-Raphson & Metode Secant Untuk Mencari Akar Persamaan Dalam Sistem Persamaan Non-Linier. Petir, 13(1), 72–79. https://doi.org/10.33322/petir.v13i1.893
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Copyright (c) 2024 Eva Mindasari, Sawaluddin, Parapat Gultom
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Muhammad Khoiruddin harahap
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