Titlebook: Artificial Evolution; Third European Confe Jin-Kao Hao,Evelyne Lutton,Dominique Snyers Conference proceedings 1998 Springer-Verlag Berlin H

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Large-Scale Manipulative Experiments (GA). We give first a review of the work on these measures such as the epistasis correlation. Then we try to relate the epistasis correlation to the overall performances of a binary GA on a set of 14 functions. The only relation that seems to hold strongly is that a high epistasis correlation impli

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Large-Scale Manipulative Experiments done in two steps. First, the fitness landscape to be optimized is analyzed. Secondly, the performance of different search procedures is described. The insight gained from the fitness landscape analysis is related to the performance of the different search procedures.

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Adaptive penalties for evolutionary graph coloring,pendent way to handle constrained problems. Second, it leads to superior EA performance. In an extensive series of comparative experiments we show that the SAW-ing EA outperforms a powerful graph coloring heuristic algorithm, DSatur, on the hardest graph instances and has a linear scale-up behaviour.