Immigrant schemes for evolutionary algorithms in dynamic environments: Adapting the replacement rate
Immigrant schemes for evolutionary algorithms in dynamic environments: Adapting the replacement rate
复制标题
DOI：
10.1007/s11432-011-4211-1
复制
发表时间：
2011-04
期刊：
影响因子：
--
通讯作者：
Xin Yu;K. Tang;X. Yao
中科院分区：
文献类型：
--
作者：
Xin Yu;K. Tang;X. Yao
进化算法（EA）解决动态优化问题（DOP）的一种方法是通过引入移民来维持人口的多样性。到目前为止，所有为就业区制定的移民计划都采用固定替代率。本文研究了动态环境中替代率对移民计划区绩效的影响，并提出了移民计划区区的自适应机制来解决DOP问题。我们的实验研究表明，新方法可以避免微调参数的繁琐工作，并且在大多数情况下优于使用传统建议值的固定替代率的其他移民方案。
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.