A comparative analysis on the performance of particle swarm optimization and artificial immune systems for mathematical test functions

David F.W. Yap, S. P. Koh, S. K. Tiong

Research output: Contribution to journalArticle

2 Citations (Scopus)


Over the years, the area of Artificial Immune Systems (AIS) has drawn wide attention among researchers as the algorithm is able to enhance local searching ability and efficiency. Alternatively, Particle Swarm Optimization (PSO) has been used effectively in solving optimization problems. This paper compares the optimization results of the mathematical functions using AIS and PSO. The numerical results show that both PSO and AIS give comparable fitness solutions with the former performing about 56 percent faster than the latter. Conversely, for simpler mathematical functions, AIS performs marginally faster than PSO at about 14 percent while maintaining good accuracy of the objective value.

Original languageEnglish
Pages (from-to)4344-4350
Number of pages7
JournalAustralian Journal of Basic and Applied Sciences
Issue number4
Publication statusPublished - 01 Oct 2009


All Science Journal Classification (ASJC) codes

  • General

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