Effective linkage learning using low-order statistics and clustering
IEEE Transactions on Evolutionary Computation - Special issue on evolutionary algorithms based on probabilistic models
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Diversity preservation has already been established as an important concern for evolutionaly computation. Clus- tering techniques were, among others, successfully applied to this purpose. Another important aspect of the research on evolutiomly computation is related to linkage learning - the detection of the problem structure avoiding disruption of building blocks when new individuals are generated. This paper presents a novel approach which is a nav estimation of distribution algorithm (EDA) where clustering plays two robs: diversity preservation and linkage learning. Initial empirical investigations illustrate the behmior of the algo- rithm when solving two benchmark optimization problems. 1.