Evolutionary Dynamic Multi-objective Optimisation: A Survey
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.
|ESI Research Field|
Cited Times [WOS]:4
|Document Type||Journal Article|
|Department||Department of Computer Science and Engineering|
1.University of Aberdeen
3.De Montfort University
4.Southern University of Science and Technology
Shouyong,Jiang,Juan,Zou,Shengxiang,Yang,et al. Evolutionary Dynamic Multi-objective Optimisation: A Survey[J]. ACM COMPUTING SURVEYS,2022,55(4):1-47.
Shouyong,Jiang,Juan,Zou,Shengxiang,Yang,&Xin,Yao.(2022).Evolutionary Dynamic Multi-objective Optimisation: A Survey.ACM COMPUTING SURVEYS,55(4),1-47.
Shouyong,Jiang,et al."Evolutionary Dynamic Multi-objective Optimisation: A Survey".ACM COMPUTING SURVEYS 55.4(2022):1-47.
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