{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,28]],"date-time":"2026-03-28T13:00:30Z","timestamp":1774702830640,"version":"3.50.1"},"reference-count":55,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Applied Soft Computing"],"published-print":{"date-parts":[[2026,4]]},"DOI":"10.1016\/j.asoc.2026.114687","type":"journal-article","created":{"date-parts":[[2026,1,21]],"date-time":"2026-01-21T16:04:44Z","timestamp":1769011484000},"page":"114687","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["A structure-guided framework for multimodal optimization leveraging chaotic search and persistence-based clustering"],"prefix":"10.1016","volume":"192","author":[{"given":"Xiang","family":"Meng","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1545-9204","authenticated-orcid":false,"given":"Yan","family":"Pei","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"78","reference":[{"key":"10.1016\/j.asoc.2026.114687_bib0005","series-title":"Proceedings of the 1999 Congress on Evolutionary Computation-Cec99","first-page":"1633","article-title":"Multinational evolutionary algorithms","volume":"vol. 3","author":"Ursem","year":"1999"},{"key":"10.1016\/j.asoc.2026.114687_bib0010","series-title":"PPSN","first-page":"27","article-title":"Crowding and preselection revisited","volume":"vol. 2","author":"Mahfoud","year":"1992"},{"issue":"9","key":"10.1016\/j.asoc.2026.114687_bib0015","doi-asserted-by":"crossref","first-page":"1455","DOI":"10.1016\/S0031-3203(99)00137-5","article-title":"Genetic algorithm-based clustering technique","volume":"33","author":"Maulik","year":"2000","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.asoc.2026.114687_bib0020","series-title":"Proceedings of the 2002 Congress on Evolutionary Computation. CEC\u201902 (Cat. No. 02TH8600)","first-page":"825","article-title":"Scalable multi-objective optimization test problems","volume":"vol. 1","author":"Deb","year":"2002"},{"issue":"4","key":"10.1016\/j.asoc.2026.114687_bib0025","doi-asserted-by":"crossref","first-page":"518","DOI":"10.1109\/TEVC.2016.2638437","article-title":"Seeking multiple solutions: an updated survey on niching methods and their applications","volume":"21","author":"Li","year":"2016","journal-title":"IEEE Trans. Evol. Comput."},{"key":"10.1016\/j.asoc.2026.114687_bib0030","series-title":"Molecular Evolutionary Genetics","author":"Nei","year":"1987"},{"key":"10.1016\/j.asoc.2026.114687_bib0035","doi-asserted-by":"crossref","first-page":"341","DOI":"10.1023\/A:1008202821328","article-title":"Differential evolution\u2013a simple and efficient heuristic for global optimization over continuous spaces","volume":"11","author":"Storn","year":"1997","journal-title":"J. Glob. Optim."},{"key":"10.1016\/j.asoc.2026.114687_bib0040","series-title":"Proceedings of ICNN\u201995 - International Conference on Neural Networks","first-page":"1942","article-title":"Particle swarm optimization","volume":"vol. 4","author":"Kennedy","year":"1995"},{"issue":"3","key":"10.1016\/j.asoc.2026.114687_bib0045","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1109\/TEVC.2003.810069","article-title":"Chaotic sequences to improve the performance of evolutionary algorithms","volume":"7","author":"Caponetto","year":"2003","journal-title":"IEEE Trans. Evol. Comput."},{"key":"10.1016\/j.asoc.2026.114687_bib0050","series-title":"Evolutionary Algorithms and Chaotic Systems","volume":"vol. 267","author":"Zelinka","year":"2010"},{"issue":"5","key":"10.1016\/j.asoc.2026.114687_bib0055","doi-asserted-by":"crossref","first-page":"2110","DOI":"10.1016\/j.chaos.2007.06.084","article-title":"Differential evolution algorithm-based parameter estimation for chaotic systems","volume":"39","author":"Peng","year":"2009","journal-title":"Chaos Solit. Fractals"},{"issue":"9","key":"10.1016\/j.asoc.2026.114687_bib0060","first-page":"2687","article-title":"Chaotic harmony search algorithms","volume":"216","author":"Alatas","year":"2010","journal-title":"Appl. Math. Comput."},{"issue":"3","key":"10.1016\/j.asoc.2026.114687_bib0065","doi-asserted-by":"crossref","first-page":"97","DOI":"10.1109\/4235.735432","article-title":"Fitness sharing and niching methods revisited","volume":"2","author":"Sareni","year":"1998","journal-title":"IEEE Trans. Evol. Comput."},{"key":"10.1016\/j.asoc.2026.114687_bib0070","first-page":"41","article-title":"Genetic algorithms with sharing for multimodal function optimization","author":"Goldberg","year":"1987"},{"key":"10.1016\/j.asoc.2026.114687_bib0075","series-title":"Niching Methods for Genetic Algorithms","author":"Mahfoud","year":"1995"},{"key":"10.1016\/j.asoc.2026.114687_bib0080","series-title":"Proceedings of the 7th Annual Conference on Genetic and Evolutionary Computation","first-page":"873","article-title":"Efficient differential evolution using speciation for multimodal function optimization","author":"Li","year":"2005"},{"key":"10.1016\/j.asoc.2026.114687_bib0085","series-title":"IEEE Congress on Evolutionary Computation","first-page":"1","article-title":"Species based evolutionary algorithms for multimodal optimization: a brief review","author":"Li","year":"2010"},{"key":"10.1016\/j.asoc.2026.114687_bib0090","series-title":"2013 IEEE Congress on Evolutionary Computation","first-page":"79","article-title":"A dynamic archive niching differential evolution algorithm for multimodal optimization","author":"Epitropakis","year":"2013"},{"issue":"11","key":"10.1016\/j.asoc.2026.114687_bib0095","first-page":"5421","article-title":"Differential evolution for multimodal optimization with species by nearest-better clustering","volume":"51","author":"Lin","year":"2021","journal-title":"IEEE Trans. Cybern."},{"key":"10.1016\/j.asoc.2026.114687_bib0100","article-title":"Differential evolution with nearest density clustering for multimodal optimization problems","volume":"640","author":"Zhao","year":"2023","journal-title":"Inf. Sci."},{"key":"10.1016\/j.asoc.2026.114687_bib0105","article-title":"Attribute and network community detection based competitive differential evolution for multimodal optimization problems","volume":"642","author":"Chen","year":"2023","journal-title":"Inf. Sci."},{"key":"10.1016\/j.asoc.2026.114687_bib0110","series-title":"Proc. IEEE Congress on Evolutionary Computation (CEC)","first-page":"2593","article-title":"Running up those hills: multi-modal search with the niching migratory multi-swarm optimiser","author":"Fieldsend","year":"2014"},{"issue":"3","key":"10.1016\/j.asoc.2026.114687_bib0115","doi-asserted-by":"crossref","first-page":"527","DOI":"10.1109\/TEVC.2021.3117116","article-title":"Static and dynamic multimodal optimization by improved covariance matrix self-adaptation evolution strategy with repelling subpopulations","volume":"26","author":"Ahrari","year":"2022","journal-title":"IEEE Trans. Evol. Comput."},{"key":"10.1016\/j.asoc.2026.114687_bib0120","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1016\/j.neucom.2019.01.006","article-title":"A multilevel sampling strategy based memetic differential evolution for multimodal optimization","volume":"334","author":"Wang","year":"2019","journal-title":"Neurocomputing"},{"key":"10.1016\/j.asoc.2026.114687_bib0125","series-title":"Proc. IEEE Congress on Evolutionary Computation (CEC)","first-page":"1","article-title":"Differential evolution with adaptive niching for multimodal optimization","author":"Brest","year":"2011"},{"issue":"1","key":"10.1016\/j.asoc.2026.114687_bib0130","doi-asserted-by":"crossref","first-page":"114","DOI":"10.1109\/TEVC.2019.2910721","article-title":"Automatic niching differential evolution with contour prediction approach for multimodal optimization problems","volume":"24","author":"Wang","year":"2019","journal-title":"IEEE Trans. Evol. Comput."},{"key":"10.1016\/j.asoc.2026.114687_bib0135","doi-asserted-by":"crossref","DOI":"10.1016\/j.asoc.2023.110218","article-title":"Strengthening evolution-based differential evolution with prediction strategy for multimodal optimization and its application in multi-robot task allocation","volume":"139","author":"Zhao","year":"2023","journal-title":"Appl. Soft Comput."},{"issue":"5","key":"10.1016\/j.asoc.2026.114687_bib0140","first-page":"887","article-title":"An efficient surrogate-assisted particle swarm differential evolution for expensive multimodal optimization","volume":"24","author":"Wang","year":"2020","journal-title":"IEEE Trans. Evol. Comput."},{"issue":"7","key":"10.1016\/j.asoc.2026.114687_bib0145","doi-asserted-by":"crossref","first-page":"6707","DOI":"10.1109\/TCYB.2020.3032995","article-title":"Hybridizing niching, particle swarm optimization, and evolution strategy for multimodal optimization","volume":"52","author":"Luo","year":"2020","journal-title":"IEEE Trans. Cybern."},{"key":"10.1016\/j.asoc.2026.114687_bib0150","series-title":"Proceedings of the IEEE International Conference on Evolutionary Computation (ICEC\u201996)","first-page":"798","article-title":"A clearing procedure as a niching method for genetic algorithms","author":"Petrowski","year":"1996"},{"key":"10.1016\/j.asoc.2026.114687_bib0155","author":"Hansen"},{"key":"10.1016\/j.asoc.2026.114687_bib0160","first-page":"141","article-title":"A modern introduction to memetic algorithms","author":"Moscato","year":"2010"},{"issue":"3","key":"10.1016\/j.asoc.2026.114687_bib0165","doi-asserted-by":"crossref","first-page":"439","DOI":"10.1162\/evco_a_00182","article-title":"Multimodal optimization by covariance matrix self-adaptation evolution strategy with repelling subpopulations","volume":"25","author":"Ahrari","year":"2017","journal-title":"Evol. Comput."},{"issue":"4","key":"10.1016\/j.asoc.2026.114687_bib0170","doi-asserted-by":"crossref","first-page":"455","DOI":"10.1023\/A:1008306431147","article-title":"Efficient global optimization of expensive black-box functions","volume":"13","author":"Jones","year":"1998","journal-title":"J. Glob. Optim."},{"issue":"2","key":"10.1016\/j.asoc.2026.114687_bib0175","doi-asserted-by":"crossref","first-page":"182","DOI":"10.1109\/4235.996017","article-title":"A fast and elitist multiobjective genetic algorithm: nsga-ii","volume":"6","author":"Deb","year":"2002","journal-title":"IEEE Trans. Evol. Comput."},{"key":"10.1016\/j.asoc.2026.114687_bib0180","series-title":"2016 IEEE Congress on Evolutionary Computation (CEC)","first-page":"2454","article-title":"Multimodal multi-objective optimization: a preliminary study","author":"Liang","year":"2016"},{"issue":"1","key":"10.1016\/j.asoc.2026.114687_bib0185","first-page":"98","article-title":"Hierarchy ranking method for multimodal multiobjective optimization with local pareto fronts","volume":"26","author":"Li","year":"2022","journal-title":"IEEE Trans. Evol. Comput."},{"issue":"5","key":"10.1016\/j.asoc.2026.114687_bib0190","doi-asserted-by":"crossref","first-page":"805","DOI":"10.1109\/TEVC.2017.2754271","article-title":"A multiobjective particle swarm optimizer using ring topology for solving multimodal multiobjective problems","volume":"22","author":"Yue","year":"2018","journal-title":"IEEE Trans. Evol. Comput."},{"key":"10.1016\/j.asoc.2026.114687_bib0195","series-title":"Advances in Swarm Intelligence: 9th International Conference, ICSI 2018, Shanghai, China, June 17-22, 2018, Proceedings, Part I 9","first-page":"550","article-title":"A self-organizing multi-objective particle swarm optimization algorithm for multimodal multi-objective problems","author":"Liang","year":"2018"},{"issue":"7","key":"10.1016\/j.asoc.2026.114687_bib0200","doi-asserted-by":"crossref","first-page":"1544","DOI":"10.1109\/JAS.2023.123609","article-title":"Coevolutionary framework for generalized multimodal multi-objective optimization","volume":"10","author":"Li","year":"2023","journal-title":"IEEE\/CAA J. Autom. Sin."},{"issue":"5","key":"10.1016\/j.asoc.2026.114687_bib0205","doi-asserted-by":"crossref","first-page":"773","DOI":"10.1109\/TEVC.2016.2519378","article-title":"A reference vector guided evolutionary algorithm for many-objective optimization","volume":"20","author":"Cheng","year":"2016","journal-title":"IEEE Trans. Evol. Comput."},{"issue":"6","key":"10.1016\/j.asoc.2026.114687_bib0210","doi-asserted-by":"crossref","first-page":"1064","DOI":"10.1109\/TEVC.2021.3078441","article-title":"Weighted indicator-based evolutionary algorithm for multimodal multiobjective optimization","volume":"25","author":"Li","year":"2021","journal-title":"IEEE Trans. Evol. Comput."},{"issue":"2","key":"10.1016\/j.asoc.2026.114687_bib0215","doi-asserted-by":"crossref","first-page":"474","DOI":"10.1109\/TETCI.2022.3221940","article-title":"Balancing convergence and diversity in objective and decision spaces for multimodal multi-objective optimization","volume":"7","author":"Ming","year":"2023","journal-title":"IEEE Trans. Emerg. Top. Comput. Intell."},{"issue":"6","key":"10.1016\/j.asoc.2026.114687_bib0220","first-page":"935","article-title":"A survey of evolutionary algorithms for multi-modal multi-objective optimization","volume":"25","author":"Liu","year":"2021","journal-title":"IEEE Trans. Evol. Comput."},{"issue":"12","key":"10.1016\/j.asoc.2026.114687_bib0225","doi-asserted-by":"crossref","first-page":"15217","DOI":"10.1007\/s10462-023-10526-z","article-title":"A comprehensive survey on nsga-ii for multi-objective optimization and applications","volume":"56","author":"Ma","year":"2023","journal-title":"Artif. Intell. Rev."},{"issue":"1","key":"10.1016\/j.asoc.2026.114687_bib0230","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1162\/EVCO_a_00042","article-title":"Multimodal optimization using a bi-objective evolutionary algorithm","volume":"20","author":"Deb","year":"2012","journal-title":"Evol. Comput."},{"issue":"4","key":"10.1016\/j.asoc.2026.114687_bib0235","doi-asserted-by":"crossref","first-page":"631","DOI":"10.1109\/TEVC.2021.3103936","article-title":"An ensemble surrogate-based framework for expensive multiobjective evolutionary optimization","volume":"26","author":"Lin","year":"2021","journal-title":"IEEE Trans. Evol. Comput."},{"issue":"1","key":"10.1016\/j.asoc.2026.114687_bib0240","doi-asserted-by":"crossref","first-page":"74","DOI":"10.1109\/TEVC.2018.2802784","article-title":"A classification-based surrogate-assisted evolutionary algorithm for expensive many-objective optimization","volume":"23","author":"Pan","year":"2018","journal-title":"IEEE Trans. Evol. Comput."},{"key":"10.1016\/j.asoc.2026.114687_bib0245","series-title":"2024 IEEE Congress on Evolutionary Computation (CEC)","first-page":"1","article-title":"Evolutionary multi-modal optimization using persistence-based clustering in riemannian manifolds","author":"Meng","year":"2024"},{"key":"10.1016\/j.asoc.2026.114687_bib0250","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1007\/s11047-013-9409-2","article-title":"Chaotic evolution: fusion of chaotic ergodicity and evolutionary iteration for optimization","volume":"13","author":"Pei","year":"2014","journal-title":"Nat. Comput."},{"issue":"33","key":"10.1016\/j.asoc.2026.114687_bib0255","first-page":"8","article-title":"Benchmark functions for the CEC 2013 special session and competition on large-scale global optimization","volume":"7","author":"Li","year":"2013","journal-title":"gene"},{"issue":"3","key":"10.1016\/j.asoc.2026.114687_bib0260","first-page":"425","article-title":"Multimodal optimization using a pareto-dominance based differential evolution approach","volume":"16","author":"Deb","year":"2019","journal-title":"IEEE Trans. Evol. Comput."},{"key":"10.1016\/j.asoc.2026.114687_bib0265","series-title":"Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No. 04TH8753)","first-page":"1382","article-title":"Multimodal optimization using crowding-based differential evolution","volume":"vol. 2","author":"Thomsen","year":"2004"},{"key":"10.1016\/j.asoc.2026.114687_bib0270","series-title":"Problem Definitions and Evaluation Criteria for the Cec 2020 Special Session on Multimodal Multiobjective Optimization","author":"Liang","year":"2019"},{"key":"10.1016\/j.asoc.2026.114687_bib0275","series-title":"International Conference on Evolutionary Multi-Criterion Optimization","first-page":"110","article-title":"Modified distance calculation in generational distance and inverted generational distance","author":"Ishibuchi","year":"2015"}],"container-title":["Applied Soft Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1568494626001353?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1568494626001353?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,3,28]],"date-time":"2026-03-28T12:46:30Z","timestamp":1774701990000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1568494626001353"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4]]},"references-count":55,"alternative-id":["S1568494626001353"],"URL":"https:\/\/doi.org\/10.1016\/j.asoc.2026.114687","relation":{},"ISSN":["1568-4946"],"issn-type":[{"value":"1568-4946","type":"print"}],"subject":[],"published":{"date-parts":[[2026,4]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"A structure-guided framework for multimodal optimization leveraging chaotic search and persistence-based clustering","name":"articletitle","label":"Article Title"},{"value":"Applied Soft Computing","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.asoc.2026.114687","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"114687"}}