IEEE Transactions on Evolutionary Computation
Genetic approaches for graph partitioning: a survey
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Quotient geometric crossovers and redundant encodings
Theoretical Computer Science
Representations for evolutionary algorithms
Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
Representations for evolutionary algorithms
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
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Normalization transforms one parent genotype to be consistent with the other before crossover. In this paper, we explain how normalization alleviates the difficulties caused by nonsynonymously redundant encodings in genetic algorithms. We define the encodings with maximally nonsynonymous property and prove that the encodings induce uncorrelated search spaces. Extensive experiments for a number of problems show that normalization transforms the uncorrelated search spaces to correlated ones and leads to significant improvement in performance.