{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T02:29:38Z","timestamp":1783045778916,"version":"3.54.6"},"reference-count":72,"publisher":"Springer Science and Business Media LLC","issue":"15","license":[{"start":{"date-parts":[[2019,12,23]],"date-time":"2019-12-23T00:00:00Z","timestamp":1577059200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2019,12,23]],"date-time":"2019-12-23T00:00:00Z","timestamp":1577059200000},"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":[[2020,8]]},"DOI":"10.1007\/s00500-019-04631-x","type":"journal-article","created":{"date-parts":[[2019,12,23]],"date-time":"2019-12-23T19:02:49Z","timestamp":1577127769000},"page":"11695-11713","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":47,"title":["Multivector particle swarm optimization algorithm"],"prefix":"10.1007","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9170-3291","authenticated-orcid":false,"given":"Hussam N.","family":"Fakhouri","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Amjad","family":"Hudaib","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Azzam","family":"Sleit","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2019,12,23]]},"reference":[{"issue":"10","key":"4631_CR1","doi-asserted-by":"crossref","first-page":"13170","DOI":"10.1016\/j.eswa.2011.04.126","volume":"38","author":"B Alatas","year":"2011","unstructured":"Alatas B (2011) ACROA: artificial chemical reaction optimization algorithm for global optimization. Expert Syst Appl 38(10):13170\u201313180","journal-title":"Expert Syst Appl"},{"issue":"8","key":"4631_CR2","doi-asserted-by":"crossref","first-page":"98","DOI":"10.5539\/mas.v11n8p98","volume":"11","author":"RM Al-Sayyed","year":"2017","unstructured":"Al-Sayyed RM, Fakhouri HN, Rodan A, Pattinson C (2017) Polar particle swarm algorithm for solving cloud data migration optimization problem. Mod Appl Sci 11(8):98","journal-title":"Mod Appl Sci"},{"key":"4631_CR3","doi-asserted-by":"crossref","first-page":"163","DOI":"10.1007\/978-981-13-0341-8_15","volume-title":"Advances in computer communication and computational sciences","author":"EV Altay","year":"2019","unstructured":"Altay EV, Alatas B (2019) Performance comparisons of socially inspired metaheuristic algorithms on unconstrained global optimization. In: Advances in computer communication and computational sciences. Springer, Singapore, pp 163\u2013175"},{"key":"4631_CR4","volume-title":"Recent developments in metaheuristics","year":"2018","unstructured":"Amodeo L, Talbi EG, Yalaoui F (eds) (2018) Recent developments in metaheuristics. Springer, New York"},{"issue":"3","key":"4631_CR5","doi-asserted-by":"crossref","first-page":"715","DOI":"10.1007\/s00500-018-3102-4","volume":"23","author":"S Arora","year":"2019","unstructured":"Arora S, Singh S (2019) Butterfly optimization algorithm: a novel approach for global optimization. Soft Comput 23(3):715\u2013734","journal-title":"Soft Comput"},{"key":"4631_CR6","doi-asserted-by":"crossref","unstructured":"Atashpaz-Gargari E, Lucas C (2007) Imperialist competitive algorithm: an algorithm for optimization inspired by imperialistic competition. In: IEEE congress on evolutionary computation. IEEE, pp 4661\u20134667","DOI":"10.1109\/CEC.2007.4425083"},{"key":"4631_CR8","doi-asserted-by":"crossref","unstructured":"Ben\u00edtez-Hidalgo A, Nebro AJ, Durillo JJ, Garc\u00eda-Nieto J, L\u00f3pez-Camacho E, Barba-Gonz\u00e1lez C, Aldana-Montes JF (2018) About designing an observer pattern-based architecture for a multi-objective metaheuristic optimization framework. In: International symposium on intelligent and distributed computing. Springer, Cham, pp 50\u201360","DOI":"10.1007\/978-3-319-99626-4_5"},{"key":"4631_CR9","doi-asserted-by":"crossref","first-page":"209","DOI":"10.1016\/j.swevo.2017.10.004","volume":"39","author":"Y Chen","year":"2018","unstructured":"Chen Y, Li L, Peng H, Xiao J, Wu Q (2018) Dynamic multi-swarm differential learning particle swarm optimizer. Swarm Evolut Comput 39:209\u2013221","journal-title":"Swarm Evolut Comput"},{"issue":"4","key":"4631_CR10","doi-asserted-by":"crossref","first-page":"919","DOI":"10.1109\/TFUZZ.2013.2278972","volume":"22","author":"NJ Cheung","year":"2013","unstructured":"Cheung NJ, Ding XM, Shen HB (2013) OptiFel: a convergent heterogeneous particle swarm optimization algorithm for Takagi-Sugeno fuzzy modeling. IEEE Trans Fuzzy Syst 22(4):919\u2013933","journal-title":"IEEE Trans Fuzzy Syst"},{"key":"4631_CR11","doi-asserted-by":"crossref","unstructured":"Dai C, Zhu Y, Chen W (2006) Seeker optimization algorithm. In: International conference on computational and information science. Springer, Berlin, pp 167\u2013176","DOI":"10.1109\/ICCIAS.2006.294126"},{"key":"4631_CR12","volume-title":"Evolutionary algorithms in engineering applications","year":"2013","unstructured":"Dasgupta D, Michalewicz Z (eds) (2013) Evolutionary algorithms in engineering applications. Springer, NewYork"},{"issue":"4","key":"4631_CR13","doi-asserted-by":"crossref","first-page":"236","DOI":"10.1007\/s00500-004-0377-4","volume":"9","author":"K Deb","year":"2005","unstructured":"Deb K (2005) A population-based algorithm-generator for real-parameter optimization. Soft Comput 9(4):236\u2013253","journal-title":"Soft Comput"},{"key":"4631_CR14","doi-asserted-by":"crossref","unstructured":"Dorigo M, Di Caro G (1999) Ant colony optimization: a new meta-heuristic. In: Proceedings of the 1999 congress on evolutionary computation-CEC99 (Cat. No. 99TH8406), vol 2. IEEE, pp 1470\u20131477","DOI":"10.1109\/CEC.1999.782657"},{"key":"4631_CR15","doi-asserted-by":"crossref","unstructured":"Du H, Wu X, Zhuang J (2006) Small-world optimization algorithm for function optimization. In: International conference on natural computation. Springer, Berlin, pp 264\u2013273","DOI":"10.1007\/11881223_33"},{"key":"4631_CR16","doi-asserted-by":"crossref","first-page":"585","DOI":"10.1016\/j.asoc.2014.03.043","volume":"22","author":"MA Eita","year":"2014","unstructured":"Eita MA, Fahmy MM (2014) Group counseling optimization. Appl Soft Comput 22:585\u2013604","journal-title":"Appl Soft Comput"},{"issue":"2","key":"4631_CR17","doi-asserted-by":"crossref","first-page":"106","DOI":"10.1016\/j.advengsoft.2005.04.005","volume":"37","author":"OK Erol","year":"2006","unstructured":"Erol OK, Eksin I (2006) A new optimization method: big bang\u2013big crunch. Adv Eng Softw 37(2):106\u2013111","journal-title":"Adv Eng Softw"},{"key":"4631_CR18","doi-asserted-by":"crossref","first-page":"151","DOI":"10.1016\/j.compstruc.2012.07.010","volume":"110","author":"H Eskandar","year":"2012","unstructured":"Eskandar H, Sadollah A, Bahreininejad A, Hamdi M (2012) Water cycle algorithm\u2014a novel metaheuristic optimization method for solving constrained engineering optimization problems. Comput Struct 110:151\u2013166","journal-title":"Comput Struct"},{"key":"4631_CR19","doi-asserted-by":"crossref","first-page":"425","DOI":"10.2528\/PIER07082403","volume":"77","author":"RA Formato","year":"2007","unstructured":"Formato RA (2007) Central force optimization: a new metaheuristic with applications in applied electromagnetics. Prog Electromagn Res 77:425\u2013491","journal-title":"Prog Electromagn Res"},{"key":"4631_CR200","doi-asserted-by":"publisher","DOI":"10.1080\/0952813X.2019.1694591","author":"SN Fakhouri","year":"2019","unstructured":"Fakhouri SN, Hudaib A, Fakhouri HN (2019) Enhanced optimizer algorithm and its application to software testing. J Exp Theor Artif Intell. https:\/\/doi.org\/10.1080\/0952813X.2019.1694591","journal-title":"J Exp Theor Artif Intell"},{"issue":"4","key":"4631_CR20","doi-asserted-by":"crossref","first-page":"1168","DOI":"10.1016\/j.isatra.2014.03.018","volume":"53","author":"AH Gandomi","year":"2014","unstructured":"Gandomi AH (2014) Interior search algorithm (ISA): a novel approach for global optimization. ISA Trans 53(4):1168\u20131183","journal-title":"ISA Trans"},{"issue":"2","key":"4631_CR21","doi-asserted-by":"crossref","first-page":"60","DOI":"10.1177\/003754970107600201","volume":"76","author":"ZW Geem","year":"2001","unstructured":"Geem ZW, Kim JH, Loganathan GV (2001) A new heuristic optimization algorithm: harmony search. Simulation 76(2):60\u201368","journal-title":"Simulation"},{"key":"4631_CR22","doi-asserted-by":"crossref","first-page":"177","DOI":"10.1016\/j.asoc.2014.02.006","volume":"19","author":"N Ghorbani","year":"2014","unstructured":"Ghorbani N, Babaei E (2014) Exchange market algorithm. Appl Soft Comput 19:177\u2013187","journal-title":"Appl Soft Comput"},{"issue":"3","key":"4631_CR23","doi-asserted-by":"crossref","first-page":"190","DOI":"10.1287\/ijoc.1.3.190","volume":"1","author":"F Glover","year":"1989","unstructured":"Glover F (1989) Tabu search\u2014part I. ORSA J Comput 1(3):190\u2013206","journal-title":"ORSA J Comput"},{"key":"4631_CR24","first-page":"70","volume-title":"Tabu search","author":"F Glover","year":"1993","unstructured":"Glover F, Laguna M (1993) Tabu search. Wiley, New York, pp 70\u2013150"},{"key":"4631_CR25","doi-asserted-by":"crossref","first-page":"175","DOI":"10.1016\/j.ins.2012.08.023","volume":"222","author":"A Hatamlou","year":"2013","unstructured":"Hatamlou A (2013) Black hole: a new heuristic optimization approach for data clustering. Inf Sci 222:175\u2013184","journal-title":"Inf Sci"},{"key":"4631_CR26","doi-asserted-by":"crossref","unstructured":"He S, Wu QH, Saunders JR (2006) A novel group search optimizer inspired by animal behavioural ecology. In: 2006 IEEE international conference on evolutionary computation. IEEE, pp 1272\u20131278","DOI":"10.1109\/CEC.2006.1688455"},{"issue":"1","key":"4631_CR27","doi-asserted-by":"crossref","first-page":"66","DOI":"10.1038\/scientificamerican0792-66","volume":"267","author":"JH Holland","year":"1992","unstructured":"Holland JH (1992) Genetic algorithms. Sci Am 267(1):66\u201373","journal-title":"Sci Am"},{"issue":"1","key":"4631_CR28","doi-asserted-by":"crossref","first-page":"32","DOI":"10.5539\/mas.v12n1p32","volume":"12","author":"AA Hudaib","year":"2018","unstructured":"Hudaib AA, Fakhouri HN (2018) Supernova optimizer: a novel natural inspired meta-heuristic. Mod Appl Sci 12(1):32\u201350","journal-title":"Mod Appl Sci"},{"key":"4631_CR29","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1007\/978-3-319-74775-0_2","volume-title":"A metaheuristic approach to protein structure prediction","author":"ND Jana","year":"2018","unstructured":"Jana ND, Das S, Sil J (2018) Metaheuristic approach to PSP\u2014an overview of the existing state-of-the-art. In: A metaheuristic approach to protein structure prediction. Springer, Cham, pp 29\u201338"},{"issue":"14","key":"4631_CR30","doi-asserted-by":"crossref","first-page":"5619","DOI":"10.1007\/s00500-018-3218-6","volume":"23","author":"D Janiga","year":"2019","unstructured":"Janiga D, Czarnota R, Stopa J, Wojnarowski P, Kosowski P (2019) Utilization of nature-inspired algorithms for gas condensate reservoir optimization. Soft Comput 23(14):5619\u20135631","journal-title":"Soft Comput"},{"issue":"3","key":"4631_CR31","doi-asserted-by":"crossref","first-page":"235","DOI":"10.3233\/FI-2017-1539","volume":"153","author":"H Joshi","year":"2017","unstructured":"Joshi H, Arora S (2017) Enhanced grey wolf optimization algorithm for global optimization. Fundamenta Informaticae 153(3):235\u2013264","journal-title":"Fundamenta Informaticae"},{"issue":"6","key":"4631_CR32","doi-asserted-by":"crossref","first-page":"1643","DOI":"10.1007\/s00521-015-1962-4","volume":"27","author":"VK Kamboj","year":"2016","unstructured":"Kamboj VK (2016) A novel hybrid PSO\u2013GWO approach for unit commitment problem. Neural Comput Appl 27(6):1643\u20131655","journal-title":"Neural Comput Appl"},{"issue":"3","key":"4631_CR33","doi-asserted-by":"crossref","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 Global Optim 39(3):459\u2013471","journal-title":"J Global Optim"},{"key":"4631_CR34","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1016\/j.advengsoft.2013.03.004","volume":"59","author":"A Kaveh","year":"2013","unstructured":"Kaveh A, Farhoudi N (2013) A new optimization method: Dolphin echolocation. Adv Eng Softw 59:53\u201370","journal-title":"Adv Eng Softw"},{"key":"4631_CR35","doi-asserted-by":"crossref","first-page":"283","DOI":"10.1016\/j.compstruc.2012.09.003","volume":"112","author":"A Kaveh","year":"2012","unstructured":"Kaveh A, Khayatazad M (2012) A new meta-heuristic method: ray optimization. Comput Struct 112:283\u2013294","journal-title":"Comput Struct"},{"key":"4631_CR36","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1016\/j.compstruc.2014.04.005","volume":"139","author":"A Kaveh","year":"2014","unstructured":"Kaveh A, Mahdavi VR (2014) Colliding bodies optimization: a novel meta-heuristic method. Comput Struct 139:18\u201327","journal-title":"Comput Struct"},{"issue":"3\u20134","key":"4631_CR37","doi-asserted-by":"crossref","first-page":"267","DOI":"10.1007\/s00707-009-0270-4","volume":"213","author":"A Kaveh","year":"2010","unstructured":"Kaveh A, Talatahari S (2010) A novel heuristic optimization method: charged system search. Acta Mech 213(3\u20134):267\u2013289","journal-title":"Acta Mech"},{"key":"4631_CR38","doi-asserted-by":"crossref","first-page":"760","DOI":"10.1007\/978-0-387-30164-8_630","volume-title":"Encyclopedia of machine learning","author":"J Kennedy","year":"2011","unstructured":"Kennedy J (2011) Particle swarm optimization. Encyclopedia of machine learning. Springer, US, pp 760\u2013766"},{"issue":"19","key":"4631_CR39","doi-asserted-by":"crossref","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(19):6686\u20136698","journal-title":"Expert Syst Appl"},{"issue":"4598","key":"4631_CR40","doi-asserted-by":"crossref","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(4598):671\u2013680","journal-title":"Science"},{"issue":"8","key":"4631_CR41","first-page":"32","volume":"13","author":"JR Koza","year":"1994","unstructured":"Koza JR (1994) Genetic programming II: automatic discovery of reusable subprograms. Cambridge 13(8):32","journal-title":"Cambridge"},{"key":"4631_CR42","first-page":"1","volume-title":"Handbook of research on emergent applications of optimization algorithms","author":"K Krawiec","year":"2018","unstructured":"Krawiec K, Simons C, Swan J, Woodward J (2018) Metaheuristic design patterns: new perspectives for larger-scale search architectures. In: Vasant P, Alparslan-Gok SZ, Weber GW (eds) Handbook of research on emergent applications of optimization algorithms. IGI Global, Hershey, PA, pp 1\u201336"},{"issue":"1","key":"4631_CR43","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1504\/IJCISTUDIES.2009.025340","volume":"1","author":"KN Krishnanand","year":"2009","unstructured":"Krishnanand KN, Ghose D (2009) Glowworm swarm optimization: a new method for optimising multi-modal functions. Int J Comput Intell Stud 1(1):93\u2013119","journal-title":"Int J Comput Intell Stud"},{"key":"4631_CR44","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1016\/j.advengsoft.2016.01.008","volume":"95","author":"S Mirjalili","year":"2016","unstructured":"Mirjalili S, Lewis A (2016) The whale optimization algorithm. Adv Eng Softw 95:51\u201367","journal-title":"Adv Eng Softw"},{"key":"4631_CR45","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1016\/j.advengsoft.2013.12.007","volume":"69","author":"S Mirjalili","year":"2014","unstructured":"Mirjalili S, Mirjalili SM, Lewis A (2014) Grey wolf optimizer. Adv Eng Softw 69:46\u201361","journal-title":"Adv Eng Softw"},{"issue":"11","key":"4631_CR46","doi-asserted-by":"crossref","first-page":"1097","DOI":"10.1016\/S0305-0548(97)00031-2","volume":"24","author":"N Mladenovi\u0107","year":"1997","unstructured":"Mladenovi\u0107 N, Hansen P (1997) Variable neighborhood search. Comput Oper Res 24(11):1097\u20131100","journal-title":"Comput Oper Res"},{"key":"4631_CR47","unstructured":"Moghaddam FF, Moghaddam RF, Cheriet M (2012) Curved space optimization: a random search based on general relativity theory. arXiv preprint arXiv:1208.2214"},{"key":"4631_CR100","doi-asserted-by":"crossref","first-page":"174","DOI":"10.1016\/j.measurement.2015.12.011","volume":"81","author":"OA Mohamed","year":"2016","unstructured":"Mohamed OA, Masood SH, Bhowmik JL (2016) Optimization of fused deposition modeling process parameters for dimensional accuracy using I-optimality criterion. Measurement 81:174\u2013196","journal-title":"Measurement"},{"key":"4631_CR48","doi-asserted-by":"crossref","first-page":"190","DOI":"10.1016\/j.epsr.2016.09.025","volume":"142","author":"AAA Mohamed","year":"2017","unstructured":"Mohamed AAA, Mohamed YS, El-Gaafary AA, Hemeida AM (2017) Optimal power flow using moth swarm algorithm. Electr Power Syst Res 142:190\u2013206","journal-title":"Electr Power Syst Res"},{"issue":"7","key":"4631_CR49","doi-asserted-by":"crossref","first-page":"2087","DOI":"10.1016\/j.camwa.2010.07.049","volume":"60","author":"R Oftadeh","year":"2010","unstructured":"Oftadeh R, Mahjoob MJ, Shariatpanahi M (2010) A novel meta-heuristic optimization algorithm inspired by group hunting of animals: hunting search. Comput Math Appl 60(7):2087\u20132098","journal-title":"Comput Math Appl"},{"key":"4631_CR51","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1016\/j.knosys.2011.07.001","volume":"26","author":"WT Pan","year":"2012","unstructured":"Pan WT (2012) A new fruit fly optimization algorithm: taking the financial distress model as an example. Knowl Based Syst 26:69\u201374","journal-title":"Knowl Based Syst"},{"key":"4631_CR52","doi-asserted-by":"crossref","first-page":"454","DOI":"10.1016\/B978-008045157-2\/50081-X","volume-title":"Proceedings of the second international virtual conference on intelligent production machines and systems (IPROMS 2006)","author":"DT Pham","year":"2006","unstructured":"Pham DT, Ghanbarzadeh A, Ko\u00e7 E, Otri S, Rahim S, Zaidi M (2006) The bees algorithm\u2014a novel tool for complex optimization problems. In: Proceedings of the second international virtual conference on intelligent production machines and systems (IPROMS 2006). Elsevier, Oxford, pp 454\u2013459"},{"key":"4631_CR53","doi-asserted-by":"crossref","first-page":"504","DOI":"10.1016\/j.asoc.2018.05.006","volume":"69","author":"MH Qais","year":"2018","unstructured":"Qais MH, Hasanien HM, Alghuwainem S (2018) Augmented grey wolf optimizer for grid-connected PMSG-based wind energy conversion systems. Appl Soft Comput 69:504\u2013515","journal-title":"Appl Soft Comput"},{"issue":"8","key":"4631_CR54","doi-asserted-by":"crossref","first-page":"5508","DOI":"10.1016\/j.asoc.2011.05.008","volume":"11","author":"R Rajabioun","year":"2011","unstructured":"Rajabioun R (2011) Cuckoo optimization algorithm. Appl Soft Comput 11(8):5508\u20135518","journal-title":"Appl Soft Comput"},{"issue":"5","key":"4631_CR55","doi-asserted-by":"crossref","first-page":"2837","DOI":"10.1016\/j.asoc.2012.05.018","volume":"13","author":"F Ramezani","year":"2013","unstructured":"Ramezani F, Lotfi S (2013) Social-based algorithm (SBA). Appl Soft Comput 13(5):2837\u20132856","journal-title":"Appl Soft Comput"},{"issue":"1","key":"4631_CR56","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.ins.2011.08.006","volume":"183","author":"RV Rao","year":"2012","unstructured":"Rao RV, Savsani VJ, Vakharia DP (2012) Teaching\u2013learning-based optimization: an optimization method for continuous non-linear large scale problems. Inf Sci 183(1):1\u201315","journal-title":"Inf Sci"},{"issue":"13","key":"4631_CR57","doi-asserted-by":"crossref","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(13):2232\u20132248","journal-title":"Inf Sci"},{"key":"4631_CR58","first-page":"83","volume-title":"Evolutions strategies","author":"I Rechenberg","year":"1978","unstructured":"Rechenberg I (1978) Evolutions strategies. Springer, Berlin, pp 83\u2013114"},{"key":"4631_CR59","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.physrep.2016.08.001","volume":"655","author":"S Salcedo-Sanz","year":"2016","unstructured":"Salcedo-Sanz S (2016) Modern meta-heuristics based on nonlinear physics processes: a review of models and design procedures. Phys Rep 655:1\u201370","journal-title":"Phys Rep"},{"issue":"1\u20132","key":"4631_CR60","first-page":"132","volume":"6","author":"H Shah-Hosseini","year":"2011","unstructured":"Shah-Hosseini H (2011) Principal components analysis by the galaxy-based search algorithm: a novel metaheuristic for continuous optimisation. Int J Comput Sci Eng 6(1\u20132):132\u2013140","journal-title":"Int J Comput Sci Eng"},{"issue":"6","key":"4631_CR61","doi-asserted-by":"crossref","first-page":"702","DOI":"10.1109\/TEVC.2008.919004","volume":"12","author":"D Simon","year":"2008","unstructured":"Simon D (2008) Biogeography-based optimization. IEEE Trans Evol Comput 12(6):702\u2013713","journal-title":"IEEE Trans Evol Comput"},{"issue":"1","key":"4631_CR62","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1111\/itor.12001","volume":"22","author":"K S\u00f6rensen","year":"2015","unstructured":"S\u00f6rensen K (2015) Metaheuristics\u2014the metaphor exposed. Int Trans Oper Res 22(1):3\u201318","journal-title":"Int Trans Oper Res"},{"key":"4631_CR63","unstructured":"S\u00f6rensen K, Sevaux M, Glover F (2018) A history of metaheuristics. In: Handbook of heuristics. Springer, pp 1\u201318"},{"key":"4631_CR64","first-page":"355","volume-title":"International conference in swarm intelligence","author":"Y Tan","year":"2010","unstructured":"Tan Y, Zhu Y (2010) Fireworks algorithm for optimization. In: International conference in swarm intelligence. Springer, Berlin, Heidelberg, pp 355\u2013364"},{"issue":"8","key":"4631_CR65","doi-asserted-by":"crossref","first-page":"937","DOI":"10.1016\/j.ins.2005.02.003","volume":"176","author":"F Van den Bergh","year":"2006","unstructured":"Van den Bergh F, Engelbrecht AP (2006) A study of particle swarm optimization particle trajectories. Inf Sci 176(8):937\u2013971","journal-title":"Inf Sci"},{"key":"4631_CR66","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1007\/978-94-015-7744-1_2","volume-title":"Simulated annealing: theory and applications","author":"PJ Van Laarhoven","year":"1987","unstructured":"Van Laarhoven PJ, Aarts EH (1987) Simulated annealing. Simulated annealing: theory and applications. Springer, Dordrecht, pp 7\u201315"},{"key":"4631_CR67","unstructured":"Webster B, Bernhard PJ (2003) A local search optimization algorithm based on natural principles of gravitation. In: Proceedings of the 2003 international conference on information and knowledge engineering (IKE\u201903), pp 255\u2013261"},{"key":"4631_CR69","unstructured":"Yang XS (2010a) Firefly algorithm in engineering optimization"},{"key":"4631_CR70","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1007\/978-3-642-12538-6_6","volume-title":"Nature inspired cooperative strategies for optimization (NICSO 2010)","author":"XS Yang","year":"2010","unstructured":"Yang XS (2010b) A new metaheuristic bat-inspired algorithm. Nature inspired cooperative strategies for optimization (NICSO 2010). Springer, Berlin, pp 65\u201374"},{"key":"4631_CR71","unstructured":"Yang XS, Deb S (2009) Cuckoo search via L\u00e9vy flights. In: 2009 World congress on nature & biologically inspired computing (NaBIC). IEEE, pp 210\u2013214"},{"issue":"2","key":"4631_CR72","doi-asserted-by":"crossref","first-page":"82","DOI":"10.1109\/4235.771163","volume":"3","author":"X Yao","year":"1999","unstructured":"Yao X, Liu Y, Lin G (1999) Evolutionary programming made faster. IEEE Trans Evol Comput 3(2):82\u2013102","journal-title":"IEEE Trans Evol Comput"},{"key":"4631_CR73","doi-asserted-by":"crossref","first-page":"283","DOI":"10.1016\/j.knosys.2018.08.030","volume":"163","author":"W Zhao","year":"2019","unstructured":"Zhao W, Wang L, Zhang Z (2019) Atom search optimization and its application to solve a hydrogeologic parameter estimation problem. Knowl Based Syst 163:283\u2013304","journal-title":"Knowl Based Syst"}],"container-title":["Soft Computing"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00500-019-04631-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s00500-019-04631-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00500-019-04631-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,7,29]],"date-time":"2024-07-29T02:50:59Z","timestamp":1722221459000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s00500-019-04631-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,12,23]]},"references-count":72,"journal-issue":{"issue":"15","published-print":{"date-parts":[[2020,8]]}},"alternative-id":["4631"],"URL":"https:\/\/doi.org\/10.1007\/s00500-019-04631-x","relation":{},"ISSN":["1432-7643","1433-7479"],"issn-type":[{"value":"1432-7643","type":"print"},{"value":"1433-7479","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,12,23]]},"assertion":[{"value":"23 December 2019","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":"The authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"This article does not contain any studies with human participants or animals performed by any of the authors.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}}]}}