Abstract
Differential Evolution (DE) is an efficient optimizer in current use. Although many new DE mutant vectors have been proposed by alter the differential operator, there are few works studying the differential operator’s effect in DE algorithm. This paper proposes a correlation between the DE performance and the mutant vector. That is, for a particular mutant vector, increase the number of differential operator would influence the performance of the algorithm linearly. These mutant vectors are evaluated by 23 benchmarks selected from Congress on Evolutionary Computation (CEC) competition. Additionally, this paper proposes an unrestrained method to generate mutant vector. Unlike the old method selects mutually exclusive individuals, the new method allows same individuals appear repeatedly to generate mutant vector. This new method could enhance the potential diversity of the population and improve the performance of DE in general. abstract environment.
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Liu, H., Huang, H., Liu, S. (2012). Explore Influence of Differential Operator in DE Mutation with Unrestrained Method to Generate Mutant Vector. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Swarm and Evolutionary Computation. EC SIDE 2012 2012. Lecture Notes in Computer Science, vol 7269. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29353-5_34
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DOI: https://doi.org/10.1007/978-3-642-29353-5_34
Publisher Name: Springer, Berlin, Heidelberg
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