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Particle swarm optimization for minimax problems

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3 Author(s)
E. C. Laskari ; Dept. of Math., Patras Univ., Greece ; K. E. Parsopoulos ; M. N. Vrahatis

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

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Evolutionary Computation, 2002. CEC '02. Proceedings of the 2002 Congress on  (Volume:2 )

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