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During the last two years several methods have been proposed for handling nonlinear constraints by genetic algorithms for numerical optimization problems; most of them were based on penalty functions. However, the performance of these methods is highly problem-dependent; moreover, many methods require additional tuning of several parameters. We present a new optimization system (Genocop III), which is based on concepts of co-evolution and repair algorithms. We present the results of the system on a few selected test problems and discuss some directions for further research.
Michalewicz et al. (Tue,) studied this question.