{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,9]],"date-time":"2026-05-09T16:12:19Z","timestamp":1778343139868,"version":"3.51.4"},"reference-count":109,"publisher":"Oxford University Press (OUP)","issue":"5","license":[{"start":{"date-parts":[[2026,3,26]],"date-time":"2026-03-26T00:00:00Z","timestamp":1774483200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U21A20464"],"award-info":[{"award-number":["U21A20464"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62066005"],"award-info":[{"award-number":["62066005"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,5,7]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>In recent years, chaos theory has been widely incorporated into metaheuristic optimization algorithms to enhance their search performance. However, for a given algorithm, there is still a lack of systematic and large-scale comparison regarding the effectiveness of different chaotic maps, and no clear consensus has yet been reached. To address this issue, this paper reviews 12 commonly used classical chaotic maps and summarizes three typical integration strategies of chaotic maps in bio-inspired optimization algorithms. Taking the recently proposed snake optimizer, a representative bio-inspired algorithm with distinct exploration and exploitation phases, as a case study, comprehensive simulation experiments are conducted to investigate the performance impact of different chaotic maps. The proposed chaotic-map-based variants are evaluated on the CEC 2022 benchmark test functions as well as several real-world engineering design problems. The experimental results indicate that the performance improvement brought by chaotic maps is highly dependent on the map type and problem characteristics. Overall, the tent chaotic map demonstrates the most consistent and significant enhancement among the considered variants, while other maps exhibit varying levels of effectiveness. In addition, a comparative analysis of the chaotic snake optimizer is presented, highlighting its advantages, limitations, and potential directions for future research.<\/jats:p>","DOI":"10.1093\/jcde\/qwag033","type":"journal-article","created":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T12:50:34Z","timestamp":1774443034000},"page":"31-94","source":"Crossref","is-referenced-by-count":0,"title":["Comparative analysis and evaluation: A case study for multiple chaotic mapping snake optimizer"],"prefix":"10.1093","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4404-952X","authenticated-orcid":false,"given":"Yongquan","family":"Zhou","sequence":"first","affiliation":[{"name":"College of Artificial Intelligence, Guangxi Minzu University , Nanning 530006 ,","place":["China"]},{"name":"Guangxi Key Laboratories of Hybrid Computation and IC Design Analysis , Nanning 530006 ,","place":["China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qingrui","family":"Li","sequence":"additional","affiliation":[{"name":"College of Artificial Intelligence, Guangxi Minzu University , Nanning 530006 ,","place":["China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guo","family":"Zhou","sequence":"additional","affiliation":[{"name":"China University of Political Science and Law Department of Science and Technology Teaching, , Beijing 102249 ,","place":["China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qifang","family":"Luo","sequence":"additional","affiliation":[{"name":"College of Artificial Intelligence, Guangxi Minzu University , Nanning 530006 ,","place":["China"]},{"name":"Guangxi Key Laboratories of Hybrid Computation and IC Design Analysis , Nanning 530006 ,","place":["China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuanfei","family":"Wei","sequence":"additional","affiliation":[{"name":"Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia , Bangi 43600 Selangor ,","place":["Malaysia"]}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2026,3,26]]},"reference":[{"key":"2026050912022809500_bib29","doi-asserted-by":"publisher","first-page":"42","DOI":"10.1016\/j.knosys.2019.02.010","article-title":"A hyper-heuristic for improving the initial population of whale optimization algorithm","volume":"172","author":"Abd\u00a0Elaziz","year":"2019","journal-title":"Knowledge-Based Systems"},{"key":"2026050912022809500_bib1","doi-asserted-by":"publisher","first-page":"701","DOI":"10.1038\/s41598-023-50959-8","article-title":"CDMO: chaotic dwarf mongoose optimization algorithm for feature 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