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

作　　者：YU Xin TANG Ke YAO Xin 

机构地区：[1]Nature Inspired Computation and Applications Laboratory, School of Computer Science and Technology, University of Science and Technology of China, Hefei 230027, China [2]Centre of Excellence for Research in Computational Intelligence and Applications, School of Computer Science, University of Birmingham, Edgbaston, Birmingham B15 2TT, U.K.

出　　处：《Science China(Information Sciences)》2011年第7期1352-1364,共13页中国科学（信息科学）（英文版）

基　　金：partially supported by the National Natural Science Foundation of China (Grant No.U0835002);the Fund for Foreign Scholars in University Research and Teaching Programs (Grant No.B07033);an EPSRC (Grant No.EP/E058884/1) on "Evolutionary Algorithms for Dynamic Optimisation Problems:Design,Analysis and Applications";the Fund for Creative Research for Graduate Students of University of Science and Technology of China (Grant No.KD0901103)

摘　　要：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.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.

关 键 词：evolutionary algorithm dynamic optimization problem immigrant scheme self-adaptive replacement rate 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] TV62[自动化与计算机技术—控制科学与工程]