{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,5]],"date-time":"2026-01-05T14:06:23Z","timestamp":1767621983824,"version":"3.48.0"},"reference-count":49,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2026,1,3]],"date-time":"2026-01-03T00:00:00Z","timestamp":1767398400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003392","name":"Natural Science Foundation of Fujian Province","doi-asserted-by":"publisher","award":["2025J011049"],"award-info":[{"award-number":["2025J011049"]}],"id":[{"id":"10.13039\/501100003392","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information"],"abstract":"<jats:p>Achieving a dynamic equilibrium among feasibility, convergence, and diversity remains a fundamental challenge in Constrained Multi-objective Optimization Problems (CMOPs). To address the limitations of conventional methods in handling complex constraints and resource allocation, this paper proposes a Dual-Population Cooperative Evolutionary Algorithm based on Relaxed Feasibility Selection and Shrinking Contribution Resource Allocation (RFSCMOEA). First, a relaxed feasibility selection strategy is designed with a dynamically shrinking threshold, allowing near-feasible solutions to survive in early stages to enhance boundary exploration. Second, a dual-criterion environmental selection mechanism integrates non-dominated sorting with k-nearest neighbor density estimation to prevent premature convergence and ensure solution uniformity. Furthermore, a dynamic resource allocation model optimizes computational configuration by adjusting offspring generation ratios based on the real-time evolutionary contribution of each population. Extensive experiments on 47 benchmark functions and 12 real-world engineering problems demonstrate that RFSCMOEA significantly outperforms eight state-of-the-art algorithms in Feasibility Rate, Inverted Generational Distance, and Hypervolume.<\/jats:p>","DOI":"10.3390\/info17010036","type":"journal-article","created":{"date-parts":[[2026,1,5]],"date-time":"2026-01-05T10:53:50Z","timestamp":1767610430000},"page":"36","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["RFSCMOEA: A Dual-Population Cooperative Evolutionary Algorithm with Relaxed Feasibility Selection"],"prefix":"10.3390","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-8013-2726","authenticated-orcid":false,"given":"Yongchao","family":"Li","sequence":"first","affiliation":[{"name":"School of Information and Electrical Engineering, Heilongjiang Bayi Agricultural University, Daqing 163000, China"},{"name":"School of Information Engineering, Sanming University, Sanming 365004, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4339-8464","authenticated-orcid":false,"given":"Heming","family":"Jia","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Sanming University, Sanming 365004, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xinyan","family":"Lin","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Sanming University, Sanming 365004, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yaqiao","family":"Li","sequence":"additional","affiliation":[{"name":"School of Mathematical Sciences, Harbin Normal University, Harbin 150080, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qian","family":"Shi","sequence":"additional","affiliation":[{"name":"School of Mathematics and Statistics, Changchun University of Technology, Changchun 130012, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shiwei","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Mechanical and Electrical Engineering, Sanming University, Sanming 365004, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2026,1,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"101784","DOI":"10.1016\/j.swevo.2024.101784","article-title":"Two-stage bidirectional coevolutionary algorithm for constrained multi-objective optimization","volume":"92","author":"Zhao","year":"2025","journal-title":"Swarm Evol. 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