A new orthogonal array based crossover, with analysis of gene interactions, for evolutionary algorithms and its application to car door design
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Recent research shows that orthogonal array based crossovers outperform standard and existing crossovers in evolutionary algorithms in solving parametrical problems with high dimensions and multi-optima. However those crossovers employed so far, ignore the consideration of interactions between genes. In this paper, we propose a method to improve the existing orthogonal array based crossovers by integrating information of interactions between genes. It is empirically shown that the proposed orthogonal array based crossover outperforms significantly both the existing orthogonal array based crossovers and standard crossovers on solving parametrical benchmark functions that interactions exist between variables. To further compare the proposed orthogonal array based crossover with the existing crossovers in evolutionary algorithms, a validation test based on car door design is used in which the effectiveness of the proposed orthogonal array based crossover is studied.
NOTICE: this is the author’s version of a work that was accepted forpublication in Expert Systems with Applications. Changes resultingfrom the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Expert Systems with Applications, Vol. 37, no. 5 (2010) http://dx.doi.org/10.1016/j.eswa.2009.11.033
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