Abstract
This work studies a hybrid model in which an optimal search algorithm intended for discrete optimisation (A*) is combined with a heuristic algorithm for continuous optimisation (an evolution strategy). The resulting algorithm is successfully evaluated on a set of functions exhibiting different features such as multimodality, noise or epistasis. The scalability of the algorithm in the presence of epistasis is an important issue that is also studied.
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Cotta, C., Troya, J.M. (1999). Optimal discrete recombination: Hybridising evolution strategies with the A algorithm. In: Mira, J., Sánchez-Andrés, J.V. (eds) Engineering Applications of Bio-Inspired Artificial Neural Networks. IWANN 1999. Lecture Notes in Computer Science, vol 1607. Springer, Berlin, Heidelberg . https://doi.org/10.1007/BFb0100472
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DOI: https://doi.org/10.1007/BFb0100472
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