VOlUME 05 ISSUE 03 MARCH 2022
1Le Thi Bao Tran, 2Nguyen Thu Nguyet Minh, 3Tra Van Dong
1Faculty of Information Technology, Ho Chi Minh City University of Foreign Languages – Information Technology, 828 Su Van Hanh Street, Ward 13, District 10 , HCMC. Vietnam,
2,3Faculty of Fundamental Science, Van Lang University, 69/68 Dang Thuy Tram Street, Ward 13, Binh Thanh District, Ho Chi Minh City, Vietnam
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Abstract
Particel Swarm Optimization (PSO) is a form of population evolutionary algorithm introduced in the early 1995 by two American scientists, sociologist James Kennedy and electrical engineer. Russell. This thesis mainly deals with the PSO optimization algorithm and the methods of adaptive adjustment of the parameters of the PSO optimization. The thesis also presents some basic problems of PSO, from PSO history to two basic PSO algorithms and improved PSO algorithms. Some improved PSO algorithms will be presented in the thesis, including: airspeed limit, inertial weighting, and coefficient limit. These improvements are aimed at improving the quality of PSO, finding solutions to speed up the convergence of PSO.
After presenting the basic problems of the PSO algorithm, the thesis focuses on studying the influence of adjusting parameters on the ability to converge in PSO algorithms. PSO algorithms with adaptively adjusted parameters are applied in solving real function optimization problems. The results are compared with the basic PSO algorithm, showing that the methods of adaptive adjustment of the parameters improve the efficiency of the PSO algorithm in finding the optimal solutions.
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