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Although DCOPs represent the super-set of optimization problems, relatively little is understood about these problems due to the complexity added to the optimization process and few meta-heuristics exist for DCOPs. This paper proposes a co-evolutionary meta-heuristic framework to allow for easy integration of existing dynamic meta-heuristics developed to solve box-constrained dynamic optimization problems only, into the framework to produce new co-evolutionary versions of these dynamic meta-heuristics to solve various classes of DCOPs. The paper analyzes the performance of the resulting co-evolutionary versions of these existing dynamic meta-heuristics on a comprehensive set of DCOP benchmark problems, and shows that the performance of these dynamic co-evolutionary algorithms are the best performing among a number of evaluated meta-heuristics.<\/jats:p>","DOI":"10.1007\/s00500-025-10873-9","type":"journal-article","created":{"date-parts":[[2025,9,23]],"date-time":"2025-09-23T12:00:23Z","timestamp":1758628823000},"page":"5723-5770","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A co-evolutionary meta-heuristic framework for dynamic constrained optimization problems"],"prefix":"10.1007","volume":"29","author":[{"given":"Gary","family":"Pampar\u00e0","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0242-3539","authenticated-orcid":false,"given":"Andries","family":"Engelbrecht","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,9,23]]},"reference":[{"key":"10873_CR1","doi-asserted-by":"publisher","unstructured":"Ameca-Alducin M, Mezura-Montes E, Cruz-Ramirez N (2014) Differential evolution with combined variants for dynamic constrained optimization. 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