Abstract
The optimization of structures is important for many industrial applications. But the problem of structure optimization is hardly understood. In the field of evolutionary computation mostly syntactical (pure structure-based) variation operators are used. For this kind of variation operators it is difficult to integrate domain-knowledge and to control the size of a mutation step. To gain insight into the basic problems of structure optimization we analyze mutation operators for evolutionary programming. For a synthetic problem we are able to derive a semantical mutation operator. The semantical mutation operator makes use of domain knowledge and has a well-defined parameter to adjust the step size.
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Wiesmann, D. (2002). From Syntactical to Semantical Mutation Operators for Structure Optimization. In: Guervós, J.J.M., Adamidis, P., Beyer, HG., Schwefel, HP., Fernández-Villacañas, JL. (eds) Parallel Problem Solving from Nature — PPSN VII. PPSN 2002. Lecture Notes in Computer Science, vol 2439. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45712-7_23
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DOI: https://doi.org/10.1007/3-540-45712-7_23
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