文献类型：期刊文献

英文题名：Multipopulation Management in Evolutionary Algorithms and Application to Complex Warehouse Scheduling Problems

作者：Yu, Yadong[1];Ma, Haiping[1];Yu, Mei[1];Ye, Sengang[1];Chen, Xiaolei[2]

机构：[1]Shaoxing Univ, Dept Elect Engn, Shaoxing, Zhejiang, Peoples R China;[2]Chongqing Univ Posts & Telecommun, Sch Automat, Chongqing, Peoples R China

年份：2018

卷号：2018

外文期刊名：COMPLEXITY

收录：SCI-EXPANDED(收录号：WOS:000431546900001)、、EI(收录号：20182005200908)、Scopus(收录号：2-s2.0-85046781723)、WOS

语种：英文

外文摘要：Multipopulation is an effective optimization strategy which is often used in evolutionary algorithms (EAs) to improve optimization performance. However, it is of remarkable difficulty to determine the number of subpopulations during the evolution process for a given problem, which may significantly affect optimization ability of EAs. This paper proposes a simple multipopulation management strategy to dynamically adjust the subpopulation number in different evolution phases throughout the evolution. The proposed method makes use of individual distances in the same subpopulation as well as the population distances between multiple subpopulations to determine the subpopulation number, which is substantial in maintaining population diversity and enhancing the exploration ability. Furthermore, the proposed multipopulation management strategy is embedded into popular EAs to solve real-world complex automated warehouse scheduling problems. Experimental results show that the proposed multipopulation EAs can easily be implemented and outperform other regular single-population algorithms to a large extent.