Empirical Study of Segment Particle Swarm Optimization and Particle Swarm Optimization Algorithms

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Abstract

In this paper, the performance of segment particle swarm optimization (Se-PSO) algorithm was compared with that of original particle swarm optimization (PSO) algorithm. Four different benchmark functions of Sphere, Rosenbrock, Rastrigin, and Griewank with asymmetric initial range settings (upper and lower boundaries values) were selected as the test functions. The experimental results showed that, the Se-PSO algorithm achieved better results in terms of faster convergences in all the testing cases compared to the original PSO algorithm. However, the experimental results further showed the Se-PSO as a promising optimization algorithm method in some other different fields.

Item Type:	Article
Uncontrolled Keywords:	Se-PSO; PSO; sphere; Rosenbrock; Rastrigin; Griewank
Subjects:	Q Science > QA Mathematics
Faculty/Division:	Faculty of Computer System And Software Engineering
Depositing User:	Noorul Farina Arifin
Date Deposited:	04 Nov 2019 05:35
Last Modified:	04 Nov 2019 05:36
URI:	http://umpir.ump.edu.my/id/eprint/26313
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