An Adaptive Penalty Scheme In Genetic Algorithms For Constrained Optimiazation Problems

A parameter-less adaptive penalty scheme for genetic algorithms applied to constrained optimization problems is proposed. Besides being simple, adaptive and not requiring any parameter, it provides a different penalty parameter for each constraint. The performance of this new scheme is examined using several test-problems from the evolutionary computation literature.

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