{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,5]],"date-time":"2025-11-05T20:59:47Z","timestamp":1762376387587,"version":"3.37.3"},"reference-count":49,"publisher":"Springer Science and Business Media LLC","issue":"6","license":[{"start":{"date-parts":[[2018,3,24]],"date-time":"2018-03-24T00:00:00Z","timestamp":1521849600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61573258"],"award-info":[{"award-number":["61573258"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"National High-technology Research and Development Program of China","award":["2013AA103006-2"],"award-info":[{"award-number":["2013AA103006-2"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int. J. Mach. Learn. &amp; Cyber."],"published-print":{"date-parts":[[2019,6]]},"DOI":"10.1007\/s13042-018-0810-0","type":"journal-article","created":{"date-parts":[[2018,3,24]],"date-time":"2018-03-24T05:04:01Z","timestamp":1521867841000},"page":"1279-1300","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["A collaboration-based particle swarm optimizer for global optimization problems"],"prefix":"10.1007","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0336-9295","authenticated-orcid":false,"given":"Leilei","family":"Cao","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lihong","family":"Xu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Erik D.","family":"Goodman","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2018,3,24]]},"reference":[{"key":"810_CR1","unstructured":"Eberhart RC, Kennedy J (1995) A new optimizer using particle swarm theory. In: Proceedings of the Sixth International Symposium on Micro Machine and Human Science, vol 1, pp 39\u201343"},{"key":"810_CR2","unstructured":"Li X (2003) A non-dominated sorting particle swarm optimizer for multi-objective optimization. In: Proceedings of genetic and evolutionary computation conference, lecture notes in computer science. Springer, Berlin, vol 2723, pp 37\u201348"},{"key":"810_CR3","unstructured":"Chunkai Z, Yu L, Huihe S (2000) A new evolved artificial neural network and its application. In: Proceedings of the 3rd world congress on intelligent control and automation, IEEE, vol 2, pp 1065\u20131068"},{"issue":"7","key":"810_CR4","first-page":"92","volume":"1","author":"R Verma","year":"2016","unstructured":"Verma R, Mehra R (2016) PSO algorithm based adaptive median filter for noise removal in image processing application. Int J Adv Comput Sci Appl 1(7):92\u201398","journal-title":"Int J Adv Comput Sci Appl"},{"issue":"4","key":"810_CR5","doi-asserted-by":"publisher","first-page":"391","DOI":"10.1007\/s13042-012-0103-y","volume":"4","author":"S Rana","year":"2013","unstructured":"Rana S, Jasola S, Kumar R (2013) A boundary restricted adaptive particle swarm optimization for data clustering. Int J Mach Learn Cybern 4(4):391\u2013400","journal-title":"Int J Mach Learn Cybern"},{"issue":"5","key":"810_CR6","doi-asserted-by":"publisher","first-page":"576","DOI":"10.1016\/j.compbiomed.2013.01.020","volume":"43","author":"A Subasi","year":"2013","unstructured":"Subasi A (2013) Classification of EMG signals using PSO optimized SVM for diagnosis of neuromuscular disorders. Comput Biol Med 43(5):576\u2013586","journal-title":"Comput Biol Med"},{"issue":"4","key":"810_CR7","doi-asserted-by":"publisher","first-page":"225","DOI":"10.1007\/s13042-011-0021-4","volume":"2","author":"CM Lin","year":"2011","unstructured":"Lin CM, Li MC, Ting AB, Lin MH (2011) A robust self-learning PID control system design for nonlinear systems using a particle swarm optimization algorithm. Int J Mach Learn Cybern 2(4):225\u2013234","journal-title":"Int J Mach Learn Cybern"},{"key":"810_CR8","doi-asserted-by":"crossref","unstructured":"Kennedy J, Mendes R (2002) Population structure and particle swarm performance. In: Proceedings of the 2002 congress on evolutionary computation, IEEE, vol 2, pp 1671\u20131676","DOI":"10.1109\/CEC.2002.1004493"},{"key":"810_CR9","unstructured":"Kennedy J (1999) Small worlds and mega-minds: effects of neighborhood topology on particle swarm performance. In: Proceedings of the 1999 congress on evolutionary computation. IEEE, vol 3, pp 1931\u20131938"},{"issue":"6","key":"810_CR10","doi-asserted-by":"publisher","first-page":"1362","DOI":"10.1109\/TSMCB.2009.2015956","volume":"39","author":"ZH Zhan","year":"2009","unstructured":"Zhan ZH, Zhang J, Li Y et al (2009) Adaptive particle swarm optimization. IEEE Trans Syst Man Part B (Cybern) 39(6):1362\u20131381","journal-title":"IEEE Trans Syst Man Part B (Cybern)"},{"issue":"9","key":"810_CR11","doi-asserted-by":"crossref","first-page":"4560","DOI":"10.1016\/j.amc.2012.10.067","volume":"219","author":"G Xu","year":"2013","unstructured":"Xu G (2013) An adaptive parameter tuning of particle swarm optimization algorithm. Appl Math Comput 219(9):4560\u20134569","journal-title":"Appl Math Comput"},{"issue":"3","key":"810_CR12","doi-asserted-by":"publisher","first-page":"627","DOI":"10.1109\/TSMCB.2011.2171946","volume":"42","author":"C Li","year":"2012","unstructured":"Li C, Yang S, Nguyen TT, Part B (2012) A self-learning particle swarm optimizer for global optimization problems. IEEE Trans Syst Man Part B (Cybern) 42(3):627\u2013646","journal-title":"IEEE Trans Syst Man Part B (Cybern)"},{"issue":"3","key":"810_CR13","doi-asserted-by":"publisher","first-page":"281","DOI":"10.1109\/TEVC.2005.857610","volume":"10","author":"JJ Liang","year":"2006","unstructured":"Liang JJ, Qin AK, Suganthan PN et al (2006) Comprehensive learning particle swarm optimizer for global optimization of multimodal functions. IEEE Trans Evol Comput 10(3):281\u2013295","journal-title":"IEEE Trans Evol Comput"},{"key":"810_CR14","doi-asserted-by":"publisher","first-page":"43","DOI":"10.1016\/j.ins.2014.08.039","volume":"291","author":"R Cheng","year":"2015","unstructured":"Cheng R, Jin Y (2015) A social learning particle swarm optimization algorithm for scalable optimization. Inf Sci 291:43\u201360","journal-title":"Inf Sci"},{"issue":"1","key":"810_CR15","doi-asserted-by":"publisher","first-page":"150","DOI":"10.1109\/TEVC.2009.2026270","volume":"14","author":"X Li","year":"2010","unstructured":"Li X (2010) Niching without niching parameters: particle swarm optimization using a ring topology. IEEE Trans Evol Comput 14(1):150\u2013169","journal-title":"IEEE Trans Evol Comput"},{"issue":"4","key":"810_CR16","doi-asserted-by":"publisher","first-page":"440","DOI":"10.1109\/TEVC.2005.859468","volume":"10","author":"D Parrott","year":"2006","unstructured":"Parrott D, Li X (2006) Locating and tracking multiple dynamic optima by a particle swarm model using speciation. IEEE Trans Evol Comput 10(4):440\u2013458","journal-title":"IEEE Trans Evol Comput"},{"issue":"6","key":"810_CR17","doi-asserted-by":"publisher","first-page":"959","DOI":"10.1109\/TEVC.2010.2046667","volume":"14","author":"S Yang","year":"2010","unstructured":"Yang S, Li C (2010) A clustering particle swarm optimizer for locating and tracking multiple optima in dynamic environments. IEEE Trans Evol Comput 14(6):959\u2013974","journal-title":"IEEE Trans Evol Comput"},{"issue":"2","key":"810_CR18","doi-asserted-by":"publisher","first-page":"241","DOI":"10.1109\/TEVC.2011.2173577","volume":"17","author":"W Chen","year":"2013","unstructured":"Chen W, Zhang J, Lin Y et al (2013) Particle swarm optimization with an aging leader and challengers. IEEE Trans Evol Comput 17(2):241\u2013258","journal-title":"IEEE Trans Evol Comput"},{"key":"810_CR19","unstructured":"Liang JJ, Suganthan PN (2005) Dynamic multi-swarm particle swarm optimizer with local search. In: Proceedings of the 2005 IEEE congress on evolutionary computation, IEEE, vol 1, pp 522\u2013528"},{"key":"810_CR20","doi-asserted-by":"publisher","first-page":"370","DOI":"10.1016\/j.ins.2014.09.030","volume":"293","author":"Y Li","year":"2015","unstructured":"Li Y, Zhan Z, Lin S et al (2015) Competitive and cooperative particle swarm optimization with information sharing mechanism for global optimization problems. Inf Sci 293:370\u2013382","journal-title":"Inf Sci"},{"key":"810_CR21","doi-asserted-by":"publisher","first-page":"16","DOI":"10.1016\/j.ins.2012.04.028","volume":"209","author":"M Nasir","year":"2012","unstructured":"Nasir M, Das S, Maity D et al (2012) A dynamic neighborhood learning based particle swarm optimizer for global numerical optimization. Inf Sci 209:16\u201336","journal-title":"Inf Sci"},{"issue":"4","key":"810_CR22","doi-asserted-by":"publisher","first-page":"341","DOI":"10.1023\/A:1008202821328","volume":"11","author":"R Storn","year":"1997","unstructured":"Storn R, Price K (1997) Differential evolution\u2014a simple and efficient heuristic for global optimization over continuous spaces. J Glob Optimiz 11(4):341\u2013359","journal-title":"J Glob Optimiz"},{"key":"810_CR23","doi-asserted-by":"publisher","first-page":"77","DOI":"10.1016\/j.future.2017.05.044","volume":"78","author":"Y He","year":"2018","unstructured":"He Y, Xie H, Wong TL, Wang X (2018) A novel binary artificial bee colony algorithm for the set-union knapsack problem. Future Gener Comput Syst 78:77\u201386","journal-title":"Future Gener Comput Syst"},{"key":"810_CR24","doi-asserted-by":"publisher","first-page":"362","DOI":"10.1016\/j.asoc.2015.12.046","volume":"41","author":"X Li","year":"2016","unstructured":"Li X, Yang G (2016) Artificial bee colony algorithm with memory. Appl Soft Comput 41:362\u2013372","journal-title":"Appl Soft Comput"},{"issue":"3","key":"810_CR25","doi-asserted-by":"publisher","first-page":"204","DOI":"10.1109\/TEVC.2004.826074","volume":"8","author":"R Mendes","year":"2004","unstructured":"Mendes R, Kennedy J, Neves J (2004) The fully informed particle swarm: simpler, maybe better. IEEE Trans Evol Comput 8(3):204\u2013210","journal-title":"IEEE Trans Evol Comput"},{"key":"810_CR26","unstructured":"Eberhart RC, Shi Y (2001) Particle swarm optimization: development, applications and resources. In: Proceedings of the 2001 IEEE congress on evolutionary computation, IEEE, vol 1, pp 81\u201386"},{"issue":"1","key":"810_CR27","doi-asserted-by":"publisher","first-page":"4","DOI":"10.1109\/TEVC.2010.2059031","volume":"15","author":"S Das","year":"2011","unstructured":"Das S, Suganthan PN (2011) Differential evolution: a survey of the state-of-the-art. IEEE Trans Evol Comput 15(1):4\u201331","journal-title":"IEEE Trans Evol Comput"},{"issue":"4","key":"810_CR28","doi-asserted-by":"publisher","first-page":"219","DOI":"10.1504\/IJBIC.2017.087924","volume":"10","author":"H Zhu","year":"2017","unstructured":"Zhu H, He Y, Wang X (2017) Discrete differential evolutions for the discounted {0\u20131} knapsack problem. Int J Bio-Inspir Comput 10(4):219\u2013238","journal-title":"Int J Bio-Inspir Comput"},{"key":"810_CR29","doi-asserted-by":"publisher","first-page":"95","DOI":"10.1016\/j.neucom.2014.04.065","volume":"146","author":"C Dong","year":"2014","unstructured":"Dong C, Ng WWY, Wang X et al (2014) An improved differential evolution and its application to determining feature weights in similarity-based clustering. Neurocomputing 146:95\u2013103","journal-title":"Neurocomputing"},{"key":"810_CR30","doi-asserted-by":"crossref","unstructured":"Das S, Konar A, Chakraborty UK (2005) Improving particle swarm optimization with differentially perturbed velocity. In: Proceedings of the 7th annual conference on genetic and evolutionary computation. ACM, pp 177\u2013184","DOI":"10.1145\/1068009.1068037"},{"key":"810_CR31","doi-asserted-by":"crossref","unstructured":"Shi Y, Eberhart RC (1998) A modified particle swarm optimizer. In: Proceedings of 1998 IEEE world congress on computational intelligence, IEEE, pp 69\u201373","DOI":"10.1109\/ICEC.1998.699146"},{"issue":"1","key":"810_CR32","doi-asserted-by":"publisher","first-page":"58","DOI":"10.1109\/4235.985692","volume":"6","author":"M Clerc","year":"2002","unstructured":"Clerc M, Kennedy J (2002) The particle swarm-explosion, stability, and convergence in a multidimensional complex space. IEEE Trans Evol Comput 6(1):58\u201373","journal-title":"IEEE Trans Evol Comput"},{"key":"810_CR33","doi-asserted-by":"crossref","unstructured":"Shi Y, Eberhart RC (1999) Empirical study of particle swarm optimization. In: Proceedings of the 1999 congress on evolutionary computation, IEEE, vol 3, pp 1945\u20131950","DOI":"10.1109\/CEC.1999.785511"},{"issue":"3","key":"810_CR34","doi-asserted-by":"publisher","first-page":"240","DOI":"10.1109\/TEVC.2004.826071","volume":"8","author":"A Ratnaweera","year":"2004","unstructured":"Ratnaweera A, Halgamuge SK, Watson HC (2004) Self-organizing hierarchical particle swarm optimizer with time-varying acceleration coefficients. IEEE Trans Evol Comput 8(3):240\u2013255","journal-title":"IEEE Trans Evol Comput"},{"issue":"4","key":"810_CR35","doi-asserted-by":"publisher","first-page":"3658","DOI":"10.1016\/j.asoc.2011.01.037","volume":"11","author":"A Nickabadi","year":"2011","unstructured":"Nickabadi A, Ebadzadeh MM, Safabakhsh R (2011) A novel particle swarm optimization algorithm with adaptive inertia weight. Appl Soft Comput 11(4):3658\u20133670","journal-title":"Appl Soft Comput"},{"issue":"6","key":"810_CR36","doi-asserted-by":"publisher","first-page":"1272","DOI":"10.1109\/TSMCB.2005.850530","volume":"35","author":"S Janson","year":"2005","unstructured":"Janson S, Middendorf M (2005) A hierarchical particle swarm optimizer and its adaptive variant., IEEE Trans Syst Man Part B (Cybernet) 35(6):1272\u20131282","journal-title":"IEEE Trans Syst Man Part B (Cybernet)"},{"issue":"5","key":"810_CR37","first-page":"868","volume":"1","author":"KE Parsopoulos","year":"2004","unstructured":"Parsopoulos KE, Vrahatis MN (2004) UPSO: a unified particle swarm optimization scheme. Lecture Ser Comput Comput Sci Proc Int Conf Comput Methods Sci Eng 1(5):868\u2013873","journal-title":"Lecture Ser Comput Comput Sci Proc Int Conf Comput Methods Sci Eng"},{"key":"810_CR38","doi-asserted-by":"publisher","first-page":"68","DOI":"10.1016\/j.ins.2012.05.020","volume":"213","author":"M Hu","year":"2012","unstructured":"Hu M, Wu T, Weir JD (2012) An intelligent augmentation of particle swarm optimization with multiple adaptive methods. Inf Sci 213:68\u201383","journal-title":"Inf Sci"},{"issue":"5","key":"810_CR39","doi-asserted-by":"publisher","first-page":"705","DOI":"10.1109\/TEVC.2012.2232931","volume":"17","author":"M Hu","year":"2013","unstructured":"Hu M, Wu T, Weir JD (2013) An adaptive particle swarm optimization with multiple adaptive methods. IEEE Trans Evol Comput 17(5):705\u2013720","journal-title":"IEEE Trans Evol Comput"},{"issue":"20","key":"810_CR40","doi-asserted-by":"publisher","first-page":"4515","DOI":"10.1016\/j.ins.2010.07.013","volume":"181","author":"Y Wang","year":"2011","unstructured":"Wang Y, Li B, Weise T et al (2011) Self-adaptive learning based particle swarm optimization. Inf Sci 181(20):4515\u20134538","journal-title":"Inf Sci"},{"issue":"2","key":"810_CR41","doi-asserted-by":"publisher","first-page":"849","DOI":"10.1016\/j.asoc.2007.07.002","volume":"8","author":"YT Kao","year":"2008","unstructured":"Kao YT, Zahara E (2008) A hybrid genetic algorithm and particle swarm optimization for multimodal functions. Appl Soft Comput 8(2):849\u2013857","journal-title":"Appl Soft Comput"},{"key":"810_CR42","doi-asserted-by":"publisher","first-page":"131","DOI":"10.1016\/j.ins.2012.02.011","volume":"197","author":"B Qu","year":"2012","unstructured":"Qu B, Liang JJ, Suganthan PN (2012) Niching particle swarm optimization with local search for multi-modal optimization. Inf Sci 197:131\u2013143","journal-title":"Inf Sci"},{"issue":"3","key":"810_CR43","doi-asserted-by":"publisher","first-page":"387","DOI":"10.1109\/TEVC.2012.2203138","volume":"17","author":"B Qu","year":"2013","unstructured":"Qu B, Suganthan PN, Das S (2013) A distance-based locally informed particle swarm model for multimodal optimization. IEEE Trans Evol Comput 17(3):387\u2013402","journal-title":"IEEE Trans Evol Comput"},{"issue":"2","key":"810_CR44","doi-asserted-by":"publisher","first-page":"431","DOI":"10.1007\/s00500-014-1262-4","volume":"19","author":"X Liang","year":"2015","unstructured":"Liang X, Li W, Zhang Y et al (2015) An adaptive particle swarm optimization method based on clustering. Soft Comput 19(2):431\u2013448","journal-title":"Soft Comput"},{"issue":"3","key":"810_CR45","doi-asserted-by":"publisher","first-page":"225","DOI":"10.1109\/TEVC.2004.826069","volume":"8","author":"F Bergh Van den","year":"2004","unstructured":"Van den Bergh F, Engelbrecht AP (2004) A cooperative approach to particle swarm optimization. IEEE Trans Evol Comput 8(3):225\u2013239","journal-title":"IEEE Trans Evol Comput"},{"issue":"2","key":"810_CR46","doi-asserted-by":"publisher","first-page":"210","DOI":"10.1109\/TEVC.2011.2112662","volume":"16","author":"X Li","year":"2012","unstructured":"Li X, Yao X (2012) Cooperatively coevolving particle swarms for large scale optimization. IEEE Trans Evol Comput 16(2):210\u2013224","journal-title":"IEEE Trans Evol Comput"},{"key":"810_CR47","doi-asserted-by":"publisher","first-page":"119","DOI":"10.1016\/j.ins.2012.10.012","volume":"223","author":"H Wang","year":"2013","unstructured":"Wang H, Sun H, Li C et al (2013) Diversity enhanced particle swarm optimization with neighborhood search. Inf Sci 223:119\u2013135","journal-title":"Inf Sci"},{"key":"810_CR48","unstructured":"Suganthan PN, Hansen N, Liang JJ et al (2005) Problem definitions and evaluation criteria for the CEC 2005 special session on real-parameter optimization, Nanyang Technological University and KanGAL Report, p\u00a02005005"},{"issue":"3","key":"810_CR49","doi-asserted-by":"publisher","first-page":"303","DOI":"10.1109\/TEVC.2005.846356","volume":"9","author":"Y Jin","year":"2005","unstructured":"Jin Y, Branke J (2005) Evolutionary optimization in uncertain environments-a survey. IEEE Trans Evol Comput 9(3):303\u2013317","journal-title":"IEEE Trans Evol Comput"}],"container-title":["International Journal of Machine Learning and Cybernetics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-018-0810-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s13042-018-0810-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-018-0810-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,10,30]],"date-time":"2020-10-30T03:42:27Z","timestamp":1604029347000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s13042-018-0810-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,3,24]]},"references-count":49,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2019,6]]}},"alternative-id":["810"],"URL":"https:\/\/doi.org\/10.1007\/s13042-018-0810-0","relation":{},"ISSN":["1868-8071","1868-808X"],"issn-type":[{"type":"print","value":"1868-8071"},{"type":"electronic","value":"1868-808X"}],"subject":[],"published":{"date-parts":[[2018,3,24]]},"assertion":[{"value":"30 May 2017","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"17 March 2018","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 March 2018","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}