Abstract
Formation of hamming cliff hampers the progress of genetic algorithm in seemingly deceptive problems. We demonstrate through an analysis of neighbourhood search capabilities of the mutation operator in genetic algorithm that the problem can somtimes be overcome through proper genetic coding. Experiments have been conducted on a 4-bit deceptive function and the pure-integer programming problem. The integer-coded genetic algorithm performs better and requires less time than the binary-coded genetic algorithm in these problems.
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Basu, S.K., Bhatia, A.K. (2006). Mitigating Deception in Genetic Search Through Suitable Coding. In: King, I., Wang, J., Chan, LW., Wang, D. (eds) Neural Information Processing. ICONIP 2006. Lecture Notes in Computer Science, vol 4234. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11893295_104
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DOI: https://doi.org/10.1007/11893295_104
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-46484-6
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