Abstract
Numerous evolutionary computation (EC) techniques and related improvements showing effectiveness in various problem domains have been proposed in recent studies. However, it is difficult to design effective search algorithms for given target problems. It is therefore essential to construct effective search algorithms automatically. In this paper, we propose a method for evolving search algorithms using Graph Structured Program Evolution (GRAPE), which has a graph structure and is one of the automatic programming techniques developed recently. We apply the proposed method to construct search algorithms for benchmark function optimization and template matching problems. Numerical experiments show that the constructed search algorithms are effective for utilized search spaces and also for several other search spaces.
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Shirakawa, S., Nagao, T. (2009). Evolution of Search Algorithms Using Graph Structured Program Evolution. In: Vanneschi, L., Gustafson, S., Moraglio, A., De Falco, I., Ebner, M. (eds) Genetic Programming. EuroGP 2009. Lecture Notes in Computer Science, vol 5481. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01181-8_10
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DOI: https://doi.org/10.1007/978-3-642-01181-8_10
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