ABSTRACT The fitness evaluation (FE) management has been successfully applied to improve the performance of multi-population methods for dynamic optimisation problems (DOPs). In this work, we extend one of its variants to address DOPs which was recently proposed by the authors. The aim of our proposal is to increase the efficiency of the FE management. To this end, we propose a technique based on hierarchical learning automata that manages FEs at two level: at first level the algorithm decides which population should be executed, and at the second level it specifies the operation that should be performed by the selected population. A detailed experimental analysis shows the effectiveness of our proposal.

中文翻译：

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动态环境中多种群方法的两级函数评估管理模型：分层学习自动机方法

摘要 适应度评估 (FE) 管理已成功应用于改善动态优化问题 (DOP) 的多种群方法的性能。在这项工作中，我们扩展了它的一个变体来解决作者最近提出的 DOP。我们提议的目的是提高 FE 管理的效率。为此，我们提出了一种基于分层学习自动机的技术，该技术在两个级别管理 FE：第一级算法决定应该执行哪个种群，第二级它指定所选种群应该执行的操作。详细的实验分析表明了我们建议的有效性。