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Nevertheless, the question as to which search logic performs better on constrained optimization often arises. In this paper, we present\u00a0Dual Search Optimization\u00a0(DSO), a co-evolutionary algorithm that includes an adaptive penalty function to handle constrained problems. Compared to other self-adaptive metaheuristics, one of the main advantages of\u00a0DSO\u00a0is that it is able auto-construct its own perturbation logics, i.e., the ways solutions are modified to create new ones during the optimization process. This is accomplished by co-evolving the solutions (encoded as vectors of integer\/real values) and perturbation strategies (encoded as Genetic Programming trees), in order to adapt the search to the problem. In addition to that, the adaptive penalty function allows the algorithm to handle constraints very effectively, yet with a minor additional algorithmic overhead. We compare\u00a0DSO\u00a0with several algorithms from the state-of-the-art on two sets of problems, namely: (1) seven well-known constrained engineering design problems and (2) the CEC 2017 benchmark for constrained optimization. Our results show that\u00a0DSO\u00a0can achieve state-of-the-art performances, being capable to automatically adjust its behavior to the problem at hand.<\/jats:p>","DOI":"10.1007\/s00500-024-09896-5","type":"journal-article","created":{"date-parts":[[2024,7,26]],"date-time":"2024-07-26T21:05:15Z","timestamp":1722027915000},"page":"11343-11376","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["A co-evolutionary algorithm with adaptive penalty function for constrained optimization"],"prefix":"10.1007","volume":"28","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7507-1685","authenticated-orcid":false,"given":"Vin\u00edcius Veloso","family":"de Melo","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alexandre Moreira","family":"Nascimento","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9723-1830","authenticated-orcid":false,"given":"Giovanni","family":"Iacca","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,7,26]]},"reference":[{"key":"9896_CR1","unstructured":"Aguirre A, Mu\u00f1oz Zavala A, Villa Diharce E, Botello Rionda S (2007) COPSO: Constrained optimization via PSO algorithm. 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