Abstract
In this paper we show preliminary results of two efficiency enhancements proposed for Extended Compact Genetic Algorithm. First, a model building enhancement was used to reduce the complexity of the process from O(n 3) to O(n 2), speeding up the algorithm by 1000 times on a 4096 bits problem. Then, a local-search hybridization was used to reduce the population size by at least 32 times, reducing the memory and running time required by the algorithm. These results are the first steps toward a competent and efficient Genetic Algorithm.
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© 2008 Springer-Verlag Berlin Heidelberg
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Duque, T.S.P.C., Goldberg, D.E., Sastry, K. (2008). Enhancing the Efficiency of the ECGA. In: Rudolph, G., Jansen, T., Beume, N., Lucas, S., Poloni, C. (eds) Parallel Problem Solving from Nature – PPSN X. PPSN 2008. Lecture Notes in Computer Science, vol 5199. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87700-4_17
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DOI: https://doi.org/10.1007/978-3-540-87700-4_17
Publisher Name: Springer, Berlin, Heidelberg
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