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Immigrant schemes for evolutionary algorithms in dynamic environments: Adapting the replacement rate

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Abstract

One approach for evolutionary algorithms (EAs) to address dynamic optimization problems (DOPs) is to maintain diversity of the population via introducing immigrants. So far all immigrant schemes developed for EAs have used fixed replacement rates. This paper examines the impact of the replacement rate on the performance of EAs with immigrant schemes in dynamic environments, and proposes a self-adaptive mechanism for EAs with immigrant schemes to address DOPs. Our experimental study showed that the new approach could avoid the tedious work of fine-tuning the parameter and outperformed other immigrant schemes using a fixed replacement rate with traditionally suggested values in most cases.

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Authors and Affiliations

  1. Nature Inspired Computation and Applications Laboratory, School of Computer Science and Technology, University of Science and Technology of China, Hefei, 230027, China

    Xin Yu, Ke Tang & Xin Yao

  2. Centre of Excellence for Research in Computational Intelligence and Applications, School of Computer Science, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK

    Xin Yao

Authors
  1. Xin Yu
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  2. Ke Tang
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  3. Xin Yao
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Correspondence to Ke Tang.

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Yu, X., Tang, K. & Yao, X. Immigrant schemes for evolutionary algorithms in dynamic environments: Adapting the replacement rate. Sci. China Inf. Sci. 54, 1352–1364 (2011). https://doi.org/10.1007/s11432-011-4211-1

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  • DOI: https://doi.org/10.1007/s11432-011-4211-1

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