Successive Over-Relaxation Method Based on PSO

• Published in: Applied Mechanics and Materials Vol. 734; no. Electronics, Automation and Engineering of Power Systems; pp. 522 - 525
• Main Authors: Wang, Zhi Chao, Tang, Liang, Gao, Lei
• Format: Journal Article
• Language: English
• Published: Zurich Trans Tech Publications Ltd 01.02.2015
• Subjects: Algorithms; Computer simulation; Feasibility; Genetic algorithms; Genetics; Linear equations; Optimization; Searching; Iteration Method; Relaxation Factor; Genetic Algorithm (GA); Relaxation Method
• ISBN: 9783038354147; 3038354147
• ISSN: 1660-9336; 1662-7482; 1662-7482
• DOI: 10.4028/www.scientific.net/AMM.734.522

To solve large linear equations using SOR method, the most important thing is to ascertain relaxation factor. Considering current methods can not get the factor from global aspect, iteration times become larger and speed become slower. We pose a method to fix optimal factor using global search quality, genetic operational quality and compare the factor value obtaining from PSO algorithm and genetic algorithm, parabolic method. As a result, it shows that it is easier for PSO method to get optimal value than genetic and parabolic method from simulation result. PSO algorithm has huge advantage on solving global optimal problems. It is definite that PSO algorithm has great advantage then other methods and this method, and another advantage is it’s feasibility and convenience.