Proceedings of the sixth international workshop on Machine learning
Zen and the Art of Genetic Algorithms
Proceedings of the 3rd International Conference on Genetic Algorithms
Binary Representations of Integers and the Performance of Selectorecombinative Genetic Algorithms
PPSN VII Proceedings of the 7th International Conference on Parallel Problem Solving from Nature
An analysis of Gray versus binary encoding in genetic search
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Representations for Genetic and Evolutionary Algorithms
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Representation, search and genetic algorithms
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ReactGA --- the search space transformation for the local optimum escaping
HAIS'12 Proceedings of the 7th international conference on Hybrid Artificial Intelligent Systems - Volume Part I
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There has been a long debate on the "most important" operator when applying genetic algorithms. This is very closely related to the favorite binary encoding, namely standard binary or Gray. Rather than confronting both approaches, this article is motivated by the search for an encoding that supports both mutation and recombination. For this purpose an encoding scheme is proposed and evaluated both using metrics and experiments.