Matching island topologies to problem structure in parallel evolutionary algorithms
Matching island topologies to problem structure in parallel evolutionary algorithms
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DOI：
10.1007/s00500-013-0995-9
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发表时间：
2013-03
期刊：
影响因子：
4.1
通讯作者：
Ignacio Arnaldo;Iván Contreras;David Millán-Ruiz;J. Hidalgo;N. Krasnogor
中科院分区：
文献类型：
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作者：
Ignacio Arnaldo;Iván Contreras;David Millán-Ruiz;J. Hidalgo;N. Krasnogor
在并行进化算法的背景下，研究表明不同的群体结构会导致不同的搜索性能。然而，没有任何研究表明明确的证据表明求解器的群体结构与问题的网络结构之间存在相关性。在这项工作中，我们通过对大量群体结构进行清晰而系统的分析来验证这种相关性（基于众所周知的 β 图和 NK 景观问题）。此外，我们通过分析可变拓扑 EA 在动态现实问题（多技能呼叫中心）上的性能，超越了这些理想化实验中的发现。
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 knownβ-graphs andNK-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.