Evolutionary Dynamic Multi-objective Optimisation: A Survey
Evolutionary Dynamic Multi-objective Optimisation: A Survey
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DOI：
10.1145/3524495
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发表时间：
2022-03
影响因子：
16.6
通讯作者：
Shouyong Jiang;Juan Zou;Shengxiang Yang;Xin Yao
中科院分区：
文献类型：
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作者：
Shouyong Jiang;Juan Zou;Shengxiang Yang;Xin Yao
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采用进化的方法来处理多目标优化问题，具有随时间变化的目标函数，约束条件和/或环境参数的变化。由于问题中同时存在动态和多目标，EDMO的优化难度与单目标或静态优化相比有明显增加。经过近二十年的努力，EDMO在理论研究和应用等方面取得了重大进展。本文介绍了广泛的调查和分类现有的研究EDMO。多个研究机会突出，以进一步促进EDMO研究领域的发展。
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.