{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T02:15:59Z","timestamp":1760235359294,"version":"build-2065373602"},"reference-count":45,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2021,8,13]],"date-time":"2021-08-13T00:00:00Z","timestamp":1628812800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the Nature Science Foundation of the Jiangsu Higher Education Institutions of China","award":["19KJB520015"],"award-info":[{"award-number":["19KJB520015"]}]},{"name":"the Talent Development Project of Taizhou University","award":["TZXY2018QDJJ006"],"award-info":[{"award-number":["TZXY2018QDJJ006"]}]},{"name":"the Guangdong Basic and Applied Basic Research Fund Project","award":["2019A1515111139"],"award-info":[{"award-number":["2019A1515111139"]}]},{"name":"the National Science Foundation for Young Scientists of China","award":["61802274"],"award-info":[{"award-number":["61802274"]}]},{"name":"the computer science  and technology construction project of Taizhou University","award":["19YLZYA02"],"award-info":[{"award-number":["19YLZYA02"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>Brain-storm optimization (BSO), which is a population-based optimization algorithm, exhibits a poor search performance, premature convergence, and a high probability of falling into local optima. To address these problems, we developed the adaptive mechanism-based BSO (ABSO) algorithm based on the chaotic local search in this study. The adjustment of the search space using the local search method based on an adaptive self-scaling mechanism balances the global search and local development performance of the ABSO algorithm, effectively preventing the algorithm from falling into local optima and improving its convergence accuracy. To verify the stability and effectiveness of the proposed ABSO algorithm, the performance was tested using 29 benchmark test functions, and the mean and standard deviation were compared with those of five other optimization algorithms. The results showed that ABSO outperforms the other algorithms in terms of stability and convergence accuracy. In addition, the performance of ABSO was further verified through a nonparametric statistical test.<\/jats:p>","DOI":"10.3390\/a14080239","type":"journal-article","created":{"date-parts":[[2021,8,13]],"date-time":"2021-08-13T09:22:38Z","timestamp":1628846558000},"page":"239","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Adaptive Self-Scaling Brain-Storm Optimization via a Chaotic Search Mechanism"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6163-0503","authenticated-orcid":false,"given":"Zhenyu","family":"Song","sequence":"first","affiliation":[{"name":"College of Computer Science and Technology, Taizhou University, Taizhou 225300, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xuemei","family":"Yan","sequence":"additional","affiliation":[{"name":"College of Computer Science and Technology, Taizhou University, Taizhou 225300, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lvxing","family":"Zhao","sequence":"additional","affiliation":[{"name":"College of Computer Science and Technology, Taizhou University, Taizhou 225300, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Luyi","family":"Fan","sequence":"additional","affiliation":[{"name":"College of Computer Science and Technology, Taizhou University, Taizhou 225300, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8148-1509","authenticated-orcid":false,"given":"Cheng","family":"Tang","sequence":"additional","affiliation":[{"name":"Faculty of Engineering, University of Toyama, Toyama-shi 930-8555, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1985-938X","authenticated-orcid":false,"given":"Junkai","family":"Ji","sequence":"additional","affiliation":[{"name":"College of Computer Science and Software Engineering, Shenzhen University, Shenzhen 518060, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,8,13]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"9302","DOI":"10.1016\/j.apm.2016.06.013","article-title":"Adaptive memory artificial bee colony algorithm for green vehicle routing with cross-docking","volume":"40","author":"Yin","year":"2016","journal-title":"Appl. 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