{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,7]],"date-time":"2026-10-07T07:11:33Z","timestamp":1791357093962,"version":"4.3.1"},"reference-count":45,"publisher":"Springer Science and Business Media LLC","issue":"18","license":[{"start":{"date-parts":[[2020,2,26]],"date-time":"2020-02-26T00:00:00Z","timestamp":1582675200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,2,26]],"date-time":"2020-02-26T00:00:00Z","timestamp":1582675200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Soft Comput"],"published-print":{"date-parts":[[2020,9]]},"DOI":"10.1007\/s00500-020-04781-3","type":"journal-article","created":{"date-parts":[[2020,2,26]],"date-time":"2020-02-26T07:02:52Z","timestamp":1582700572000},"page":"14051-14072","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":33,"title":["An improved brainstorm optimization using chaotic opposite-based learning with disruption operator for global optimization and feature selection"],"prefix":"10.1007","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8781-7993","authenticated-orcid":false,"given":"Diego","family":"Oliva","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mohamed Abd","family":"Elaziz","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2020,2,26]]},"reference":[{"key":"4781_CR1","doi-asserted-by":"crossref","first-page":"484","DOI":"10.1016\/j.eswa.2017.07.043","volume":"90","author":"M Abd ElAziz","year":"2017","unstructured":"Abd ElAziz M, Oliva D, Xiong S (2017) An improved opposition-based sine cosine algorithm for global optimization. Exp Syst Appl 90:484\u2013500","journal-title":"Exp Syst Appl"},{"key":"4781_CR2","doi-asserted-by":"crossref","first-page":"4773","DOI":"10.1007\/s11227-017-2046-2","volume":"73","author":"LM Abualigah","year":"2017","unstructured":"Abualigah LM, Khader AT (2017) Unsupervised text feature selection technique based on hybrid particle swarm optimization algorithm with genetic operators for the text clustering. J Supercomput 73:4773\u20134795","journal-title":"J Supercomput"},{"key":"4781_CR3","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1016\/j.engappai.2018.05.003","volume":"73","author":"LM Abualigah","year":"2018","unstructured":"Abualigah LM, Khader AT, Hanandeh ES (2018a) A combination of objective functions and hybrid krill herd algorithm for text document clustering analysis. Eng Appl Artif Intell 73:111\u2013125","journal-title":"Eng Appl Artif Intell"},{"key":"4781_CR4","doi-asserted-by":"crossref","first-page":"4047","DOI":"10.1007\/s10489-018-1190-6","volume":"48","author":"LM Abualigah","year":"2018","unstructured":"Abualigah LM, Khader AT, Hanandeh ES (2018b) Hybrid clustering analysis using improved krill herd algorithm. Appl Intell 48:4047\u20134071","journal-title":"Appl Intell"},{"key":"4781_CR5","doi-asserted-by":"publisher","first-page":"456","DOI":"10.1016\/j.jocs.2017.07.018","volume":"25","author":"LM Abualigah","year":"2018","unstructured":"Abualigah LM, Khader AT, Hanandeh ES (2018c) A new feature selection method to improve the document clustering using particle swarm optimization algorithm. J Comput Sci 25:456\u2013466","journal-title":"J Comput Sci"},{"key":"4781_CR6","doi-asserted-by":"crossref","DOI":"10.1007\/978-3-030-10674-4","volume-title":"Feature selection and enhanced krill herd algorithm for text document clustering","author":"LMQ Abualigah","year":"2019","unstructured":"Abualigah LMQ (2019) Feature selection and enhanced krill herd algorithm for text document clustering. Springer, Berlin"},{"key":"4781_CR7","first-page":"19","volume":"5","author":"LMQ Abualigah","year":"2015","unstructured":"Abualigah LMQ, Hanandeh ES (2015) Applying genetic algorithms to information retrieval using vector space model. Int J Comput Sci Eng Appl 5:19","journal-title":"Int J Comput Sci Eng Appl"},{"key":"4781_CR8","doi-asserted-by":"crossref","first-page":"2531","DOI":"10.1016\/j.chaos.2009.03.196","volume":"42","author":"JM Aguirregabiria","year":"2009","unstructured":"Aguirregabiria JM (2009) Robust chaos with variable Lyapunov exponent in smooth one-dimensional maps. Chaos Solitons Fractals 42:2531\u20132539","journal-title":"Chaos Solitons Fractals"},{"key":"4781_CR9","doi-asserted-by":"crossref","first-page":"233","DOI":"10.1007\/s00521-016-2334-4","volume":"28","author":"S-A Ahmadi","year":"2017","unstructured":"Ahmadi S-A (2017) Human behavior-based optimization: a novel metaheuristic approach to solve complex optimization problems. Neural Comput Appl 28:233\u2013244","journal-title":"Neural Comput Appl"},{"key":"4781_CR10","doi-asserted-by":"publisher","DOI":"10.1155\/2015\/923698","author":"Z Cao","year":"2015","unstructured":"Cao Z, Hei X, Wang L, Shi Y, Rong X (2015) An improved brain storm optimization with differential evolution strategy for applications of ANNs. Math Prob Eng. https:\/\/doi.org\/10.1155\/2015\/923698","journal-title":"Math Prob Eng"},{"key":"4781_CR11","doi-asserted-by":"crossref","unstructured":"Chen J, Cheng S, Chen Y, Xie Y, Shi Y (2015) Enhanced brain storm optimization algorithm for wireless sensor networks deployment. In: Advances in swarm and computational intelligence, Lecture notes in computer science, vol 9140. pp 373\u2013381","DOI":"10.1007\/978-3-319-20466-6_40"},{"key":"4781_CR12","doi-asserted-by":"crossref","unstructured":"Chen J, Xie Y, Ni J (2014) Brain storm optimization model based on uncertainty information. In: 2014 Tenth international conference on computational intelligence and security (CIS). IEEE, pp 99\u2013103","DOI":"10.1109\/CIS.2014.152"},{"key":"4781_CR13","first-page":"8181","volume":"8","author":"E Cuevas","year":"2012","unstructured":"Cuevas E, Oliva D, Zaldivar D, Perez-Cisneros M, Pajares G (2012) Opposition-based electromagnetism-like for global optimization. Int J Innov Comput Inf Control 8:8181\u20138198","journal-title":"Int J Innov Comput Inf Control"},{"key":"4781_CR14","doi-asserted-by":"crossref","first-page":"20281","DOI":"10.1109\/ACCESS.2019.2897580","volume":"7","author":"W Deng","year":"2019","unstructured":"Deng W, Xu J, Zhao H (2019) An improved ant colony optimization algorithm based on hybrid strategies for scheduling problem. IEEE Access 7:20281\u201320292","journal-title":"IEEE Access"},{"key":"4781_CR15","doi-asserted-by":"crossref","first-page":"288","DOI":"10.1016\/j.asoc.2017.06.004","volume":"59","author":"W Deng","year":"2017","unstructured":"Deng W, Zhao H, Yang X, Xiong J, Sun M, Li B (2017a) Study on an improved adaptive pso algorithm for solving multi-objective gate assignment. Appl Soft Comput 59:288\u2013302","journal-title":"Appl Soft Comput"},{"key":"4781_CR16","doi-asserted-by":"crossref","first-page":"4387","DOI":"10.1007\/s00500-016-2071-8","volume":"21","author":"W Deng","year":"2017","unstructured":"Deng W, Zhao H, Zou L, Li G, Yang X, Wu D (2017b) A novel collaborative optimization algorithm in solving complex optimization problems. Soft Comput 21:4387\u20134398","journal-title":"Soft Comput"},{"issue":"8","key":"4781_CR17","doi-asserted-by":"crossref","first-page":"2441","DOI":"10.1007\/s00521-016-2804-8","volume":"30","author":"MA El Aziz","year":"2018","unstructured":"El Aziz MA, Hassanien AE (2018) An improved social spider optimization algorithm based on rough sets for solving minimum number attribute reduction problem. Neural Comput Appl 30(8):2441\u20132452","journal-title":"Neural Comput Appl"},{"issue":"4","key":"4781_CR18","doi-asserted-by":"crossref","first-page":"991","DOI":"10.1007\/s00521-017-3131-4","volume":"31","author":"AA Ewees","year":"2019","unstructured":"Ewees AA, El Aziz MA, Hassanien AE (2019) Chaotic multi-verse optimizer-based feature selection. Neural Comput Appl 31(4):991\u20131006","journal-title":"Neural Comput Appl"},{"key":"4781_CR19","unstructured":"Frank A, Asuncion A (2010) Uci machine learning repository (http:\/\/archive.ics.uci.edu\/ml). Irvine, ca: University of california. School of information and computer science 213: 2\u20132"},{"key":"4781_CR20","volume-title":"Genetic algorithms in search, optimization, and machine learning","author":"D Goldberg","year":"1989","unstructured":"Goldberg D (1989) Genetic algorithms in search, optimization, and machine learning, 1st edn. Addison-Wesley, Boston","edition":"1"},{"key":"4781_CR21","volume-title":"Astrophysical concepts","author":"M Harwit","year":"2006","unstructured":"Harwit M (2006) Astrophysical concepts. Springer, Berlin"},{"key":"4781_CR22","doi-asserted-by":"crossref","unstructured":"Jadhav H, Sharma U, Patel J, Roy R (2012) Brain storm optimization algorithm based economic dispatch considering wind power. In: 2012 IEEE International conference on power and energy (PECon). IEEE, pp 588\u2013593","DOI":"10.1109\/PECon.2012.6450282"},{"key":"4781_CR23","unstructured":"Karaboga D (2005) An idea based on honey bee swarm for numerical optimization. Technical Report TR06, Comput. Eng. Dep. Eng. Fac. Erciyes Univ"},{"key":"4781_CR24","doi-asserted-by":"crossref","unstructured":"Kennedy J, Eberhart RC (1995) Particle swarm optimization. In: IEEE proceedings of international conference on neural networks, vol 4. pp 1942\u20131948","DOI":"10.1109\/ICNN.1995.488968"},{"key":"4781_CR25","doi-asserted-by":"crossref","unstructured":"Krishnanand K, Hasani SMF, Panigrahi BK, Panda SK (2013) Optimal power flow solution using self\u2013evolving brain\u2013storming inclusive teaching\u2013learning\u2013based algorithm. In: International conference in swarm intelligence. Springer, pp 338\u2013345","DOI":"10.1007\/978-3-642-38703-6_40"},{"key":"4781_CR26","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1016\/j.engappai.2017.12.014","volume":"70","author":"M Labani","year":"2018","unstructured":"Labani M, Moradi P, Ahmadizar F, Jalili M (2018) A novel multivariate filter method for feature selection in text classification problems. Eng Appl Artif Intell 70:25\u201337","journal-title":"Eng Appl Artif Intell"},{"key":"4781_CR27","doi-asserted-by":"crossref","first-page":"3902","DOI":"10.1016\/j.cma.2004.09.007","volume":"194","author":"KS Lee","year":"2005","unstructured":"Lee KS, Geem ZW (2005) A new meta-heuristic algorithm for continuous engineering optimization: harmony search theory and practice. Comput Methods Appl Mech Eng 194:3902\u20133933","journal-title":"Comput Methods Appl Mech Eng"},{"key":"4781_CR28","first-page":"106","volume":"238","author":"H Liu","year":"2014","unstructured":"Liu H, Ding G, Wang B (2014) Bare-bones particle swarm optimization with disruption operator. Appl Math Comput 238:106\u2013122","journal-title":"Appl Math Comput"},{"key":"4781_CR29","doi-asserted-by":"crossref","first-page":"228","DOI":"10.1016\/j.knosys.2015.07.006","volume":"89","author":"S Mirjalili","year":"2015","unstructured":"Mirjalili S (2015) Moth-flame optimization algorithm: a novel nature-inspired heuristic paradigm. Knowl Based Syst 89:228\u2013249","journal-title":"Knowl Based Syst"},{"key":"4781_CR30","doi-asserted-by":"crossref","first-page":"163","DOI":"10.1016\/j.advengsoft.2017.07.002","volume":"114","author":"S Mirjalili","year":"2017","unstructured":"Mirjalili S, Gandomi AH, Mirjalili SZ, Saremi S, Faris H, Mirjalili SM (2017) Salp swarm algorithm: a bio-inspired optimizer for engineering design problems. Adv Eng Softw 114:163\u2013191","journal-title":"Adv Eng Softw"},{"key":"4781_CR31","doi-asserted-by":"crossref","first-page":"495","DOI":"10.1007\/s00521-015-1870-7","volume":"27","author":"S Mirjalili","year":"2016","unstructured":"Mirjalili S, Mirjalili SM, Hatamlou A (2016) Multi-verse optimizer: a nature-inspired algorithm for global optimization. Neural Comput Appl 27:495\u2013513","journal-title":"Neural Comput Appl"},{"key":"4781_CR32","doi-asserted-by":"crossref","first-page":"539","DOI":"10.1016\/j.scient.2011.04.003","volume":"18","author":"S Sarafrazi","year":"2011","unstructured":"Sarafrazi S, Nezamabadi-Pour H, Saryazdi S (2011) Disruption: a new operator in gravitational search algorithm. Scientia Iranica 18:539\u2013548","journal-title":"Scientia Iranica"},{"key":"4781_CR33","first-page":"303","volume-title":"Brain storm optimization algorithm","author":"Y Shi","year":"2011","unstructured":"Shi Y (2011) Brain storm optimization algorithm, vol 6728. LNCS, Berlin, pp 303\u2013309"},{"key":"4781_CR34","doi-asserted-by":"crossref","unstructured":"Shi Y (2015) Brain storm optimization algorithm in objective space. In: 2015 IEEE congress on evolutionary computation (CEC). IEEE, pp 1227\u20131234","DOI":"10.1109\/CEC.2015.7257029"},{"key":"4781_CR35","first-page":"2005","volume":"2005005","author":"PN Suganthan","year":"2005","unstructured":"Suganthan PN, Hansen N, Liang JJ, Deb K, Chen Y-P, Auger A, Tiwari S (2005) Problem definitions and evaluation criteria for the CEC 2005 special session on real-parameter optimization. KanGAL Rep 2005005:2005","journal-title":"KanGAL Rep"},{"key":"4781_CR36","doi-asserted-by":"crossref","first-page":"682","DOI":"10.1016\/j.rser.2017.08.050","volume":"81","author":"G Tian","year":"2018","unstructured":"Tian G, Zhang H, Feng Y, Wang D, Peng Y, Jia H (2018a) Green decoration materials selection under interior environment characteristics: a grey-correlation based hybrid MCDM method. Renew Sustain Energy Rev 81:682\u2013692","journal-title":"Renew Sustain Energy Rev"},{"key":"4781_CR37","doi-asserted-by":"crossref","first-page":"748","DOI":"10.1109\/TASE.2017.2690802","volume":"15","author":"G Tian","year":"2018","unstructured":"Tian G, Zhou M, Li P (2018b) Disassembly sequence planning considering fuzzy component quality and varying operational cost. IEEE Trans Autom Sci Eng 15:748\u2013760","journal-title":"IEEE Trans Autom Sci Eng"},{"key":"4781_CR38","doi-asserted-by":"crossref","unstructured":"Tizhoosh HR (2005) Opposition-based learning: a new scheme for machine intelligence. In: International conference on computational intelligence for modelling, control and automation and international conference on intelligent agents, web technologies and internet commerce (CIMCA-IAWTIC\u201906), vol 1. pp 695\u2013701","DOI":"10.1109\/CIMCA.2005.1631345"},{"key":"4781_CR39","doi-asserted-by":"crossref","first-page":"80","DOI":"10.2307\/3001968","volume":"1","author":"F Wilcoxon","year":"1945","unstructured":"Wilcoxon F (1945) Individual comparisons by ranking methods. Biom Bull 1:80\u201383","journal-title":"Biom Bull"},{"key":"4781_CR40","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1109\/4235.585893","volume":"1","author":"DH Wolpert","year":"1997","unstructured":"Wolpert DH, Macready WG (1997) No free lunch theorems for optimization. IEEE Trans Evol Comput 1:67\u201382","journal-title":"IEEE Trans Evol Comput"},{"key":"4781_CR41","doi-asserted-by":"crossref","first-page":"1366","DOI":"10.1016\/j.chaos.2006.04.057","volume":"34","author":"D Yang","year":"2007","unstructured":"Yang D, Li G, Cheng G (2007) On the efficiency of chaos optimization algorithms for global optimization. Chaos Solitons Fractals 34:1366\u20131375","journal-title":"Chaos Solitons Fractals"},{"key":"4781_CR42","doi-asserted-by":"crossref","unstructured":"Yang Z, Shi Y (2015) Brain storm optimization with chaotic operation. In: 2015 seventh international conference on advanced computational intelligence (ICACI). IEEE, pp 111\u2013115","DOI":"10.1109\/ICACI.2015.7184759"},{"key":"4781_CR43","unstructured":"Zhan Z-h, Chen W-n, Lin Y, Gong Y-j, Li Y-l, Zhang J (2013) Parameter investigation in brain storm optimization. In: 2013 IEEE symposium on swarm intelligence (SIS). IEEE, pp 103\u2013110"},{"key":"4781_CR44","doi-asserted-by":"crossref","first-page":"99263","DOI":"10.1109\/ACCESS.2019.2929094","volume":"7","author":"H Zhao","year":"2019","unstructured":"Zhao H, Zheng J, Xu J, Deng W (2019) Fault diagnosis method based on principal component analysis and broad learning system. IEEE Access 7:99263\u201399272","journal-title":"IEEE Access"},{"key":"4781_CR45","doi-asserted-by":"crossref","unstructured":"Zhou D, Shi Y, Cheng S (2012) Brain storm optimization algorithm with modified step-size and individual generation. In: International conference in swarm intelligence. Springer, pp 243\u2013252","DOI":"10.1007\/978-3-642-30976-2_29"}],"container-title":["Soft Computing"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00500-020-04781-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s00500-020-04781-3\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00500-020-04781-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,2,25]],"date-time":"2021-02-25T00:12:02Z","timestamp":1614211922000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s00500-020-04781-3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,2,26]]},"references-count":45,"journal-issue":{"issue":"18","published-print":{"date-parts":[[2020,9]]}},"alternative-id":["4781"],"URL":"https:\/\/doi.org\/10.1007\/s00500-020-04781-3","relation":{},"ISSN":["1432-7643","1433-7479"],"issn-type":[{"value":"1432-7643","type":"print"},{"value":"1433-7479","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,2,26]]},"assertion":[{"value":"26 February 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Compliance with ethical standards"}},{"value":"It is to specifically state that \u201cno competing interest are at stake and there is no conflict of interest\u201d with other people or organizations that could inappropriately influence or bias the content of the paper.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"None of the authors of this paper has a financial or personal relationship with other people or organizations that could inappropriately influence or bias the content of the paper.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Financial or personal relationship"}},{"value":"This article does not contain any studies with human participants or animals performed by any of the authors.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Human participants or animals"}}]}}