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Yazdani, D, Yazdani, D, Blanco-Davis, E and Nguyen, TT (2024) A survey of multi-population optimization algorithms for tracking the moving optimum in dynamic environments. Journal of Membrane Computing. ISSN 2523-8906
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A survey of multipopulation optimization algorithms for tracking the moving optimum in dynamic environments.pdf - Published Version Available under License Creative Commons Attribution. Download (1MB) | Preview |
Abstract
The solution spaces of many real-world optimization problems change over time. Such problems are called dynamic optimization problems (DOPs), which pose unique challenges that necessitate adaptive strategies from optimization algorithms to maintain optimal performance and responsiveness to environmental changes. Tracking the moving optimum (TMO) is an important class of DOPs where the goal is to identify and deploy the best-found solution in each environments Multi-population dynamic optimization algorithms are particularly effective at solving TMOs due to their flexible structures and potential for adaptability. These algorithms are usually complex methods that are built by assembling multiple components, each of which is responsible for addressing a specific challenge or improving the tracking performance in response to changes. This survey provides an in-depth review of multi-population dynamic optimization algorithms, focusing on describing these algorithms as a set of multiple cooperating components, the synergy between these components, and their collective effectiveness and/or efficiency in addressing the challenges of TMOs. Additionally, this survey reviews benchmarking practices within this domain and outlines promising directions for future research.
| Item Type: | Article |
|---|---|
| Subjects: | T Technology > TA Engineering (General). Civil engineering (General) |
| Divisions: | Engineering |
| Publisher: | Springer |
| SWORD Depositor: | A Symplectic |
| Date Deposited: | 08 Jul 2024 12:19 |
| Last Modified: | 08 Jul 2024 12:21 |
| DOI or ID number: | 10.1007/s41965-024-00163-y |
| URI: | https://researchonline.ljmu.ac.uk/id/eprint/23718 |
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