期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2019
卷号：10
期号：8
页码：480-485
出版社：Science and Information Society (SAI)
摘要：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.
