Metaheuristics have gained great success in academia and practice because their search logic can be applied to any problem with available solution representation, solution quality evaluation, and certain notions of locality. Manually designing metaheuristic algorithms for solving a target problem is criticized for being laborious, error-prone, and requiring intensive specialized knowledge. This gives rise to increasing interest in automated design of metaheuristic algorithms. With computing power to fully explore potential design choices, the automated design could reach and even surpass human-level design and could make high-performance algorithms accessible to a much wider range of researchers and practitioners. This paper presents a broad picture of automated design of metaheuristic algorithms, by conducting a survey on the common grounds and representative techniques in terms of design space, design strategies, performance evaluation strategies, and target problems in this field.

翻译：元启发式算法因其搜索逻辑可应用于任何具有解表示、解质量评估及局部性概念的问题，在学术界和实践中取得了巨大成功。手动设计针对目标问题的元启发式算法存在耗时费力、易出错且需深厚专业知识等缺陷，因此元启发式算法的自动化设计日益受到关注。借助计算能力充分探索潜在设计选择，自动化设计能够达到甚至超越人类水平的设计，并使高性能算法惠及更广泛的研究人员与实践者。本文通过综述该领域在设计空间、设计策略、性能评估策略及目标问题等方面的共性基础与代表性技术，全面描绘了元启发式算法自动化设计的整体图景。