Particle swarm optimization for minimax problems

Authors:
E. C. Laskari;K. E. Parsopoulos;M. N. Vrahatis
Affiliations:
Dept. of Math., Patras Univ., Greece;Dept. of Math., Patras Univ., Greece;Dept. of Math., Patras Univ., Greece
Venue:
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
Year:
2002

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Abstract

This paper investigates the ability of the Particle Swarm Optimization (PSO) method to cope with minimax problems through experiments on well-known test functions. Experimental results indicate that PSO tackles minimax problems effectively. Moreover, PSO alleviates difficulties that might be encountered by gradient-based methods, due to the nature of the minimax: objective function, and potentially lead to failure. The performance of PSO is compared with that of other established approaches, such as the sequential quadratic programming (SQP) method and a recently proposed smoothing technique.