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.

翻译：离散搜索空间的进化计算理论在过去10年中取得了重大进展。本调查总结了这一研究领域的最近一些最重要的成果。它讨论了进化算法运行时间分析的精细模型,突出了最近关于参数调整和参数控制的理论见解,并总结了随机和动态问题的最新进展。我们研究了进化算法如何优化子模块功能,我们概述了关于分配算法的最新大量结果。最后,我们介绍了漂移分析的先进情况,这是该领域最有力的分析技术之一。