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However, it is prone to rapid loss of diversity and imbalanced exploration\u2013exploitation behaviour, leading to premature convergence in local optima and limiting final solution accuracy. To overcome these drawbacks, this paper proposes a novel dynamic mean-based HBA (DM-HBA) with two enhancements: (1) a mean-based guidance strategy that maintains population diversity and allows the algorithm to escape local optima. (2) A dynamic attraction parameter enables a smooth transition from exploration to exploitation. Finally, 41 benchmark functions from the CEC\u201917 and CEC\u201922 test suites, as well as three complex real-world engineering problems, are used. Statistical analyses revealed that DM-HBA outperformed HBA on 72% of the functions, with mean improvements of 21\u201325% in best-fitness values and approximately 26\u201334% reductions in standard deviation across 30D, 50D, and 100D. For the more challenging CEC\u201922 suite, at 20D, it outperforms HBA on 75% of the functions, with a mean improvement of 8.7% and an approximately 31% standard deviation reduction, demonstrating that DM-HBA is both robust and scalable, with a well-balanced exploration\u2013exploitation process. The source code is available atGitHub<\/jats:p>","DOI":"10.1093\/jcde\/qwaf135","type":"journal-article","created":{"date-parts":[[2025,12,15]],"date-time":"2025-12-15T12:30:37Z","timestamp":1765801837000},"page":"395-461","source":"Crossref","is-referenced-by-count":2,"title":["DM-HBA: Dynamic mean-based honey badger algorithm for engineering design optimization problems"],"prefix":"10.1093","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4898-3072","authenticated-orcid":false,"given":"Shaymah Akram","family":"Yasear","sequence":"first","affiliation":[{"name":"Computer Centre, Al-Qasim Green University , Babylon 51013 ,","place":["Iraq"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2025,12,15]]},"reference":[{"key":"2026012707521646600_bib2","doi-asserted-by":"publisher","first-page":"120484","DOI":"10.1016\/j.eswa.2023.120484","article-title":"Optimization of CNN using modified honey badger algorithm for 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