Matching island topologies to problem structure in parallel evolutionary algorithms

作     者：Arnaldo, Ignacio Contreras, Ivan Millan-Ruiz, David Ignacio Hidalgo, J. Krasnogor, Natalio 

作者机构：Univ Complutense Madrid Parallel Architectures & Bioinspired Algorithms P Madrid Spain Univ Nottingham Sch Comp Sci Interdisciplinary Comp & Complex Syst ICOS Res Gr Nottingham NG7 2RD England 

出 版 物：《SOFT COMPUTING》 (Soft Comput.)

年 卷 期：2013年第17卷第7期

页      面：1209-1225页

核心收录：

学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：UK EPSRC [EP/H010432/1] Spanish Government Avanza Competitividad I+D+I [TSI-020100-2010-962, Iyelmo INNPACTO-IPT-2011-1198-430000] Direccion General de Politica Universitaria, Ministerio de Educacion, Cultura y Deporte [Orden ECD /3628/2011] Spanish Government [TIN 2008-00508] MEC CONSOLIDER [CSD00C-07-20811] EPSRC [EP/H010432/1] Funding Source: UKRI 

主　　题：Parallel Evolutionary Algorithm Island model Problem structure 

摘      要：In the context of Parallel Evolutionary Algorithms, it has been shown that different population structures induce different search performances. Nevertheless, no work has shown a clear cut evidence that there is a correlation between the solver s population structure and the problem s network structure. In this work, we verify this correlation performing a clear and systematic analysis of a large set of population structures (based on the well known beta-graphs and NK-landscape problems. Furthermore, we go beyond our findings in these idealised experiments by analysing the performance of variable-topology EAs on a dynamic real-world problem, the Multi-Skills Call Centre.