Adaptive penalties for evolutionary
نویسنده
چکیده
In this paper we consider a problem independent constraint handling mechanism, Stepwise Adaptation of Weights (SAW) and show its working on graph coloring problems. SAWing technically belongs to the penalty function based approaches and amounts to modifying the penalty function during the search. We show that it has a twofold ben-eet. First, it proves to be rather insensitive to its technical parameters, thereby providing a general, problem independent way to handle constrained problems. Second, it leads to superior EA performance. In an extensive series of comparative experiments we show that the SAWing EA outperforms a powerful graph coloring heuristic algorithm, DSatur, on the hardest graph instances and has a linear scale-up behaviour.
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