论文标题
一项关于离散优化进化算法理论的最新进展的调查
A Survey on Recent Progress in the Theory of Evolutionary Algorithms for Discrete Optimization
论文作者
论文摘要
离散搜索空间的进化计算理论在过去十年中取得了重大进展。这项调查总结了该研究领域的一些最新结果。它讨论了进化算法的运行时分析模型，重点介绍了有关参数调整和参数控制的最新理论见解，并总结了随机和动态问题的最新进展。我们考虑如何进化算法优化了子模块功能，并概述了有关分布算法估计的最新结果。最后，我们介绍了漂移分析的艺术状态，这是该领域开发的最强大的分析技术之一。
The theory of evolutionary computation for discrete search spaces has made significant progress in the last ten years. This survey summarizes some of the most important recent results in this research area. It discusses fine-grained models of runtime analysis of evolutionary algorithms, highlights recent theoretical insights on parameter tuning and parameter control, and summarizes the latest advances for stochastic and dynamic problems. We regard how evolutionary algorithms optimize submodular functions and we give an overview over the large body of recent results on estimation of distribution algorithms. Finally, we present the state of the art of drift analysis, one of the most powerful analysis technique developed in this field.
