It is our pleasure to introduce this special issue on the recent advances in the theoretical foundations of evolutionary computation (EC). While in the early days of this field, theoretical analyses inevitably focused on simplified models of evolutionary algorithms (EAs), the continuous progress made in the development of suitable mathematical techniques for the analysis now allows to derive proven statements regarding the performance of off-the-shelf metaheuristics, such as standard generational and steady-state genetic algorithms with no algorithmic simplifications. Comparisons between the performance of a given EA with the best possible one can also be made nowadays, allowing to assess whether a given algorithm may be improved upon or whether its performance is optimal for a given class of problems. Such understanding often provides insights for the design of new EAs which provably have better performance for given problems. We are glad that examples of results of this kind are present within this special issue. A total of 27 papers were submitted which were the subject of at least three independent reviews, and six manuscripts of the highest quality were selected for publication in the special issue. In the following, we provide a brief summary of these manuscripts.

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关于进化计算的理论基础的客座社论特刊

我们很高兴就进化计算 (EC) 理论基础的最新进展介绍这个特刊。虽然在该领域的早期，理论分析不可避免地集中在进化算法 (EA) 的简化模型上，但在开发适合分析的数学技术方面取得的持续进展现在允许推导出关于离线算法性能的经过验证的陈述。 -shelf元启发式，例如没有算法简化的标准分代和稳态遗传算法。现在，还可以将给定 EA 的性能与可能的最佳 EA 的性能进行比较，从而可以评估给定算法是否可以改进，或者它的性能对于给定类别的问题是否是最佳的。这种理解通常为新 EA 的设计提供见解，这些 EA 可证明对给定问题具有更好的性能。我们很高兴在本期特刊中提供了此类结果的示例。总共提交了 27 篇论文，其中至少经过了 3 次独立评审，并选出了 6 篇质量最高的手稿在特刊上发表。在下文中，我们提供了这些手稿的简要概述。