{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,17]],"date-time":"2025-10-17T14:01:56Z","timestamp":1760709716085},"reference-count":38,"publisher":"Springer Science and Business Media LLC","issue":"9","license":[{"start":{"date-parts":[[2018,9,24]],"date-time":"2018-09-24T00:00:00Z","timestamp":1537747200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int. J. Mach. Learn. & Cyber."],"published-print":{"date-parts":[[2019,9]]},"DOI":"10.1007\/s13042-018-0878-6","type":"journal-article","created":{"date-parts":[[2018,9,24]],"date-time":"2018-09-24T10:06:38Z","timestamp":1537783598000},"page":"2401-2419","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Boosting galactic swarm optimization with ABC"],"prefix":"10.1007","volume":"10","author":[{"given":"Ersin","family":"Kaya","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sait Ali","family":"Uymaz","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Baris","family":"Kocer","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2018,9,24]]},"reference":[{"issue":"1","key":"878_CR1","first-page":"75","volume":"146","author":"F Aimin","year":"2014","unstructured":"Aimin F, Wang X, He Y, Wang L (2014) A study on residence error of training an extreme learning machine and its application to evolutionary algorithms. Neurocomputing 146(1):75\u201382","journal-title":"Neurocomputing"},{"key":"878_CR2","doi-asserted-by":"publisher","first-page":"235","DOI":"10.1016\/0004-3702(89)90050-7","volume":"40","author":"LB Booker","year":"1989","unstructured":"Booker LB, Goldberg DE, Holland JH (1989) Classifier systems and genetic algorithms. Artif Intell 40:235\u2013282. \n                    https:\/\/doi.org\/10.1016\/0004-3702(89)90050-7","journal-title":"Artif Intell"},{"key":"878_CR3","doi-asserted-by":"publisher","first-page":"95","DOI":"10.1016\/j.neucom.2014.04.065","volume":"146","author":"D Chunru","year":"2014","unstructured":"Chunru D, 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":"878_CR4","unstructured":"Colorni A, Dorigo M, Maniezzo V (1992) Distributed optimization by ant colonies. In: From Anim Animat, pp 134\u2013142"},{"key":"878_CR5","doi-asserted-by":"publisher","first-page":"169","DOI":"10.1016\/j.ins.2017.07.011","volume":"417","author":"L Cui","year":"2017","unstructured":"Cui L, Li GH, Wang XZ, Lin QZ, Chen JY, Lu N, Lu J (2017) A ranking-based adaptive artificial bee colony algorithm for global numerical optimization. Inf Sci 417:169\u2013185. \n                    https:\/\/doi.org\/10.1016\/j.ins.2017.07.011","journal-title":"Inf Sci"},{"key":"878_CR6","doi-asserted-by":"publisher","first-page":"1012","DOI":"10.1016\/j.ins.2016.07.022","volume":"367","author":"LZ Cui","year":"2016","unstructured":"Cui LZ, Li GH, Lin QZ, Du ZH, Gao WF, Chen JY, Lu N (2016) A novel artificial bee colony algorithm with depth-first search framework and elite-guided search equation. Inf Sci 367:1012\u20131044. \n                    https:\/\/doi.org\/10.1016\/j.ins.2016.07.022","journal-title":"Inf Sci"},{"key":"878_CR7","doi-asserted-by":"publisher","first-page":"53","DOI":"10.1016\/j.ins.2017.05.044","volume":"414","author":"LZ Cui","year":"2017","unstructured":"Cui LZ et al (2017) A novel artificial bee colony algorithm with an adaptive population size for numerical function optimization. Inf Sci 414:53\u201367. \n                    https:\/\/doi.org\/10.1016\/j.ins.2017.05.044","journal-title":"Inf Sci"},{"key":"878_CR8","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1016\/j.swevo.2011.02.002","volume":"1","author":"J Derrac","year":"2011","unstructured":"Derrac J, Garcia S, Molina D, Herrera F (2011) A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithms. Swarm Evol Comput 1:3\u201318. \n                    https:\/\/doi.org\/10.1016\/j.swevo.2011.02.002","journal-title":"Swarm Evol Comput"},{"key":"878_CR9","doi-asserted-by":"publisher","first-page":"687","DOI":"10.1016\/j.cor.2011.06.007","volume":"39","author":"WF Gao","year":"2012","unstructured":"Gao WF, Liu SY (2012) A modified artificial bee colony algorithm. Comput Oper Res 39:687\u2013697. \n                    https:\/\/doi.org\/10.1016\/j.cor.2011.06.007","journal-title":"Comput Oper Res"},{"key":"878_CR10","doi-asserted-by":"publisher","first-page":"1011","DOI":"10.1109\/TSMCB.2012.2222373","volume":"43","author":"WF Gao","year":"2013","unstructured":"Gao WF, Liu SY, Huang LL (2013) A novel artificial bee colony algorithm based on modified search equation and orthogonal learning. IEEE Trans Cybern 43:1011\u20131024. \n                    https:\/\/doi.org\/10.1109\/Tsmcb.2012.2222373","journal-title":"IEEE Trans Cybern"},{"key":"878_CR11","doi-asserted-by":"publisher","first-page":"103","DOI":"10.3906\/elk-1210-147","volume":"23","author":"M Gunduz","year":"2015","unstructured":"Gunduz M, Kiran MS, Ozceylan E (2015) A hierarchic approach based on swarm intelligence to solve the traveling salesman problem. Turk J Electr Eng Computer Sci 23:103\u2013117. \n                    https:\/\/doi.org\/10.3906\/elk-1210-147","journal-title":"Turk J Electr Eng Computer Sci"},{"key":"878_CR12","volume-title":"Adaptation in natural and artificial systems: an introductory analysis with applications to biology, control, and artificial intelligence","author":"JH Holland","year":"1975","unstructured":"Holland JH (1975) Adaptation in natural and artificial systems: an introductory analysis with applications to biology, control, and artificial intelligence. MIT Press, Cambridge"},{"key":"878_CR13","doi-asserted-by":"publisher","first-page":"66","DOI":"10.1038\/scientificamerican0792-66","volume":"267","author":"JH Holland","year":"1992","unstructured":"Holland JH (1992) Genetic algorithms. Sci Am 267:66\u201372","journal-title":"Sci Am"},{"key":"878_CR14","doi-asserted-by":"publisher","first-page":"459","DOI":"10.1007\/s10898-007-9149-x","volume":"39","author":"D Karaboga","year":"2007","unstructured":"Karaboga D, Basturk B (2007) A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm. J Glob Optim 39:459\u2013471. \n                    https:\/\/doi.org\/10.1007\/s10898-007-9149-x","journal-title":"J Glob Optim"},{"key":"878_CR15","doi-asserted-by":"publisher","first-page":"687","DOI":"10.1016\/j.asoc.2007.05.007","volume":"8","author":"D Karaboga","year":"2008","unstructured":"Karaboga D, Basturk B (2008) On the performance of artificial bee colony (ABC) algorithm. Appl Soft Comput 8:687\u2013697. \n                    https:\/\/doi.org\/10.1016\/j.asoc.2007.05.007","journal-title":"Appl Soft Comput"},{"key":"878_CR16","doi-asserted-by":"publisher","unstructured":"Kennedy J, Eberhart R (1995) Particle swarm optimization. In: 1995 IEEE international conference on neural networks proceedings, vols 1\u20136, pp 1942\u20131948. \n                    https:\/\/doi.org\/10.1109\/Icnn.1995.488968","DOI":"10.1109\/Icnn.1995.488968"},{"key":"878_CR17","doi-asserted-by":"publisher","first-page":"6686","DOI":"10.1016\/j.eswa.2015.04.055","volume":"42","author":"MS Kiran","year":"2015","unstructured":"Kiran MS (2015) TSA: tree-seed algorithm for continuous optimization. Expert Syst Appl 42:6686\u20136698. \n                    https:\/\/doi.org\/10.1016\/j.eswa.2015.04.055","journal-title":"Expert Syst Appl"},{"key":"878_CR18","doi-asserted-by":"publisher","first-page":"671","DOI":"10.1126\/science.220.4598.671","volume":"220","author":"S Kirkpatrick","year":"1983","unstructured":"Kirkpatrick S, Gelatt CD, Vecchi MP (1983) Optimization by simulated annealing. Science 220:671\u2013680. \n                    https:\/\/doi.org\/10.1126\/science.220.4598.671","journal-title":"Science"},{"key":"878_CR19","doi-asserted-by":"publisher","first-page":"146","DOI":"10.1016\/j.asoc.2016.12.017","volume":"52","author":"GH Li","year":"2017","unstructured":"Li GH, Cui LZ, Fu XH, Wen ZK, Lu N, Lu J (2017) Artificial bee colony algorithm with gene recombination for numerical function optimization. Appl Soft Comput 52:146\u2013159. \n                    https:\/\/doi.org\/10.1016\/j.asoc.2016.12.017","journal-title":"Appl Soft Comput"},{"key":"878_CR20","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, Baskar S (2006) Comprehensive learning particle swarm optimizer for global optimization of multimodal functions. IEEE Trans Evolut Comput 10:281\u2013295. \n                    https:\/\/doi.org\/10.1109\/Tevc.2005.857610","journal-title":"IEEE Trans Evolut Comput"},{"key":"878_CR21","doi-asserted-by":"publisher","first-page":"169","DOI":"10.1016\/j.cor.2013.09.010","volume":"43","author":"M Locatelli","year":"2014","unstructured":"Locatelli M, Maischberger M, Schoen F (2014) Differential evolution methods based on local searches. Comput Oper Res 43:169\u2013180. \n                    https:\/\/doi.org\/10.1016\/j.cor.2013.09.010","journal-title":"Comput Oper Res"},{"key":"878_CR22","doi-asserted-by":"publisher","first-page":"1679","DOI":"10.1016\/j.asoc.2010.04.024","volume":"11","author":"R Mallipeddi","year":"2011","unstructured":"Mallipeddi R, Suganthan PN, Pan QK, Tasgetiren MF (2011) Differential evolution algorithm with ensemble of parameters and mutation strategies. Appl Soft Comput 11:1679\u20131696. \n                    https:\/\/doi.org\/10.1016\/j.asoc.2010.04.024","journal-title":"Appl Soft Comput"},{"key":"878_CR23","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 Evolut Comput 8:204\u2013210. \n                    https:\/\/doi.org\/10.1109\/tevc.2004.826074","journal-title":"IEEE Trans Evolut Comput"},{"key":"878_CR24","doi-asserted-by":"publisher","first-page":"115","DOI":"10.1016\/j.ins.2014.08.040","volume":"291","author":"M Mernik","year":"2015","unstructured":"Mernik M, Liu SH, Karaboga D, Crepinsek M (2015) On clarifying misconceptions when comparing variants of the artificial bee colony algorithm by offering a new implementation. Inf Sci 291:115\u2013127. \n                    https:\/\/doi.org\/10.1016\/j.ins.2014.08.040","journal-title":"Inf Sci"},{"key":"878_CR25","unstructured":"Moore PW, Venayagamoorthy GK (2006) Empirical study of an unconstrained modified particle swarm optimization. In: 2006 IEEE congress on evolutionary computation, vols 1\u20136, p 1462"},{"key":"878_CR26","doi-asserted-by":"publisher","first-page":"771","DOI":"10.1016\/j.asoc.2015.10.034","volume":"38","author":"V Muthiah-Nakarajan","year":"2016","unstructured":"Muthiah-Nakarajan V, Noel MM (2016) Galactic swarm optimization: a new global optimization metaheuristic inspired by galactic motion. Appl Soft Comput 38:771\u2013787. \n                    https:\/\/doi.org\/10.1016\/j.asoc.2015.10.034","journal-title":"Appl Soft Comput"},{"key":"878_CR27","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, Sengupta S, Halder U, Suganthan PN (2012) A dynamic neighborhood learning based particle swarm optimizer for global numerical optimization. Inf Sci 209:16\u201336. \n                    https:\/\/doi.org\/10.1016\/j.ins.2012.04.028","journal-title":"Inf Sci"},{"key":"878_CR28","doi-asserted-by":"publisher","first-page":"501","DOI":"10.1016\/j.asoc.2015.10.022","volume":"38","author":"RP Parouha","year":"2016","unstructured":"Parouha RP, Das KN (2016) A memory based differential evolution algorithm for unconstrained optimization. Appl Soft Comput 38:501\u2013517. \n                    https:\/\/doi.org\/10.1016\/j.asoc.2015.10.022","journal-title":"Appl Soft Comput"},{"key":"878_CR29","unstructured":"Parsopoulos KE, Tasoulis DK, Vrahatis MN (2004) Multiobjective optimization using parallel vector evaluated particle swarm optimization. In: Proceedings of the iasted international conference on artificial intelligence and applications, vols 1 and 2, pp 823\u2013828"},{"key":"878_CR30","doi-asserted-by":"publisher","first-page":"398","DOI":"10.1109\/TEVC.2008.927706","volume":"13","author":"AK Qin","year":"2009","unstructured":"Qin AK, Huang VL, Suganthan PN (2009) Differential evolution algorithm with strategy adaptation for global numerical optimization. IEEE Trans Evolut Comput 13:398\u2013417. \n                    https:\/\/doi.org\/10.1109\/Tevc.2008.927706","journal-title":"IEEE Trans Evolut Comput"},{"key":"878_CR31","doi-asserted-by":"publisher","first-page":"2232","DOI":"10.1016\/j.ins.2009.03.004","volume":"179","author":"E Rashedi","year":"2009","unstructured":"Rashedi E, Nezamabadi-Pour H, Saryazdi S (2009) GSA: a gravitational search algorithm. Inf Sci 179:2232\u20132248. \n                    https:\/\/doi.org\/10.1016\/j.ins.2009.03.004","journal-title":"Inf Sci"},{"key":"878_CR32","doi-asserted-by":"publisher","first-page":"303","DOI":"10.1007\/s12293-012-0096-9","volume":"4","author":"H Sharma","year":"2012","unstructured":"Sharma H, Bansal JC, Arya KV (2012) Fitness based differential evolution. Memet Comput 4:303\u2013316. \n                    https:\/\/doi.org\/10.1007\/s12293-012-0096-9","journal-title":"Memet Comput"},{"key":"878_CR33","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 Optim 11:341\u2013359. \n                    https:\/\/doi.org\/10.1023\/A:1008202821328","journal-title":"J Glob Optim"},{"key":"878_CR34","doi-asserted-by":"publisher","first-page":"153","DOI":"10.1016\/j.asoc.2015.03.003","volume":"31","author":"SA Uymaz","year":"2015","unstructured":"Uymaz SA, Tezel G, Yel E (2015) Artificial algae algorithm (AAA) for nonlinear global optimization. Appl Soft Comput 31:153\u2013171. \n                    https:\/\/doi.org\/10.1016\/j.asoc.2015.03.003","journal-title":"Appl Soft Comput"},{"key":"878_CR35","doi-asserted-by":"publisher","first-page":"25","DOI":"10.1016\/j.biosystems.2015.11.004","volume":"138","author":"SA Uymaz","year":"2015","unstructured":"Uymaz SA, Tezel G, Yel E (2015) Artificial algae algorithm with multi-light source for numerical optimization and applications. Biosystems 138:25\u201338. \n                    https:\/\/doi.org\/10.1016\/j.biosystems.2015.11.004","journal-title":"Biosystems"},{"key":"878_CR36","doi-asserted-by":"publisher","first-page":"225","DOI":"10.1016\/j.neucom.2005.05.006","volume":"68","author":"W Xizhao","year":"2005","unstructured":"Xizhao W, He Q, Chen D, Yeung D (2005) A genetic algorithm for solving the inverse problem of support vector machines. Neurocomputing 68:225\u2013238","journal-title":"Neurocomputing"},{"key":"878_CR37","unstructured":"Yang XS (2010) A new metaheuristic bat-inspired algorithm Nicso 2010. In: Nature inspired cooperative strategies for optimization, vol 284, pp 65\u201374"},{"key":"878_CR38","doi-asserted-by":"publisher","first-page":"945","DOI":"10.1109\/TEVC.2009.2014613","volume":"13","author":"JQ Zhang","year":"2009","unstructured":"Zhang JQ, Sanderson AC (2009) JADE: adaptive differential evolution with optional external archive. IEEE Trans Evolut Comput 13:945\u2013958. \n                    https:\/\/doi.org\/10.1109\/Tevc.2009.2014613","journal-title":"IEEE Trans Evolut Comput"}],"container-title":["International Journal of Machine Learning and Cybernetics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-018-0878-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s13042-018-0878-6\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-018-0878-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,9,23]],"date-time":"2019-09-23T19:30:08Z","timestamp":1569267008000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s13042-018-0878-6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,9,24]]},"references-count":38,"journal-issue":{"issue":"9","published-print":{"date-parts":[[2019,9]]}},"alternative-id":["878"],"URL":"https:\/\/doi.org\/10.1007\/s13042-018-0878-6","relation":{},"ISSN":["1868-8071","1868-808X"],"issn-type":[{"value":"1868-8071","type":"print"},{"value":"1868-808X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,9,24]]},"assertion":[{"value":"17 October 2017","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 September 2018","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 September 2018","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}