During the last few years, several methods have been proposed for handling constraints by evolutionary algorithms for parameter optimisation problems. These methods include those based on penalty functions, preservation of feasibility, decoders and repair algorithms, as well as some hybrid techniques. Most of these techniques have serious drawbacks (some of them may return infeasible solutions, others require many additional parameters, etc.). Moreover, none of these techniques has utilized knowledge about which constraints are satisfied and which are not. In this paper, we introduce a new element to evolutionary algorithms for constrained parameter optimization problems: the parent matching mechanism. The preliminary results show that the proposed technique works very well on selected test cases.
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