Evolutionary dynamic multi-objective optimisation (EDMO) is a relatively young but rapidly growing area of investigation. EDMO employs evolutionary approaches to handle multi-objective optimisation problems that have time-varying changes in objective functions, constraints, and/or environmental parameters. Due to the simultaneous presence of dynamics and multi-objectivity in problems, the optimisation difficulty for EDMO has a marked increase compared to that for single-objective or stationary optimisation. After nearly two decades of community effort, EDMO has achieved significant advancements on various topics, including theoretic research and applications. This article presents a broad survey and taxonomy of existing research on EDMO. Multiple research opportunities are highlighted to further promote the development of the EDMO research field.

进化动态多目标优化 (EDMO) 是一个相对年轻但发展迅速的研究领域。EDMO 采用进化方法来处理目标函数、约束和/或环境参数随时间变化的多目标优化问题。由于问题同时存在动态性和多目标性，EDMO 的优化难度与单目标或稳态优化相比有显着增加。经过近二十年的社区努力，EDMO 在包括理论研究和应用在内的各个主题上取得了重大进展。本文介绍了对 EDMO 现有研究的广泛调查和分类。突出多项研究机会，进一步推动EDMO研究领域的发展。