Abstract
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.
Original language | English |
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Article number | 76 |
Pages (from-to) | 1-47 |
Number of pages | 47 |
Journal | ACM Computing Surveys |
Volume | 55 |
Issue number | 4 |
DOIs | |
Publication status | Published - Nov 2022 |
Externally published | Yes |
Bibliographical note
Publisher Copyright:© 2022 Copyright held by the owner/author(s).
Keywords
- dynamic environment
- evolutionary algorithm
- evolutionary dynamic multi-objective optimisation
- Multi-objective optimisation