{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,18]],"date-time":"2026-06-18T07:32:43Z","timestamp":1781767963802,"version":"3.54.5"},"reference-count":43,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2020,7,6]],"date-time":"2020-07-06T00:00:00Z","timestamp":1593993600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,7,6]],"date-time":"2020-07-06T00:00:00Z","timestamp":1593993600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Supercomput"],"published-print":{"date-parts":[[2021,3]]},"DOI":"10.1007\/s11227-020-03378-9","type":"journal-article","created":{"date-parts":[[2020,7,6]],"date-time":"2020-07-06T09:03:52Z","timestamp":1594026232000},"page":"2844-2874","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":86,"title":["A new and fast rival genetic algorithm for feature selection"],"prefix":"10.1007","volume":"77","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6908-1038","authenticated-orcid":false,"given":"Jingwei","family":"Too","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Abdul Rahim","family":"Abdullah","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2020,7,6]]},"reference":[{"key":"3378_CR1","doi-asserted-by":"publisher","first-page":"261","DOI":"10.1016\/j.asoc.2013.09.018","volume":"18","author":"B Xue","year":"2014","unstructured":"Xue B, Zhang M, Browne WN (2014) Particle swarm optimisation for feature selection in classification: novel initialisation and updating mechanisms. Appl Soft Comput 18:261\u2013276. https:\/\/doi.org\/10.1016\/j.asoc.2013.09.018","journal-title":"Appl Soft Comput"},{"key":"3378_CR2","doi-asserted-by":"publisher","first-page":"43","DOI":"10.1016\/j.knosys.2018.05.009","volume":"154","author":"H Faris","year":"2018","unstructured":"Faris H, Mafarja MM, Heidari AA et al (2018) An efficient binary Salp Swarm Algorithm with crossover scheme for feature selection problems. Knowl Based Syst 154:43\u201367. https:\/\/doi.org\/10.1016\/j.knosys.2018.05.009","journal-title":"Knowl Based Syst"},{"key":"3378_CR3","doi-asserted-by":"publisher","first-page":"54","DOI":"10.1016\/j.neucom.2016.03.101","volume":"213","author":"E Emary","year":"2016","unstructured":"Emary E, Zawbaa HM, Hassanien AE (2016) Binary ant lion approaches for feature selection. Neurocomputing 213:54\u201365. https:\/\/doi.org\/10.1016\/j.neucom.2016.03.101","journal-title":"Neurocomputing"},{"key":"3378_CR4","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-016-2818-2","author":"H Faris","year":"2017","unstructured":"Faris H, Hassonah MA, Al-Zoubi AM et al (2017) A multi-verse optimizer approach for feature selection and optimizing SVM parameters based on a robust system architecture. Neural Comput Appl. https:\/\/doi.org\/10.1007\/s00521-016-2818-2","journal-title":"Neural Comput Appl"},{"key":"3378_CR5","doi-asserted-by":"publisher","first-page":"e0150652","DOI":"10.1371\/journal.pone.0150652","volume":"11","author":"HM Zawbaa","year":"2016","unstructured":"Zawbaa HM, Emary E, Grosan C (2016) Feature selection via chaotic antlion optimization. PLoS ONE 11:e0150652. https:\/\/doi.org\/10.1371\/journal.pone.0150652","journal-title":"PLoS ONE"},{"key":"3378_CR6","doi-asserted-by":"publisher","first-page":"964","DOI":"10.1016\/j.asoc.2018.07.040","volume":"71","author":"I Aljarah","year":"2018","unstructured":"Aljarah I, Mafarja M, Heidari AA et al (2018) Asynchronous accelerating multi-leader salp chains for feature selection. Appl Soft Comput 71:964\u2013979. https:\/\/doi.org\/10.1016\/j.asoc.2018.07.040","journal-title":"Appl Soft Comput"},{"key":"3378_CR7","doi-asserted-by":"publisher","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. https:\/\/doi.org\/10.1016\/j.engappai.2017.12.014","journal-title":"Eng Appl Artif Intell"},{"key":"3378_CR8","doi-asserted-by":"publisher","first-page":"267","DOI":"10.1016\/j.eswa.2018.09.015","volume":"117","author":"M Mafarja","year":"2019","unstructured":"Mafarja M, Aljarah I, Faris H et al (2019) Binary grasshopper optimisation algorithm approaches for feature selection problems. Expert Syst Appl 117:267\u2013286. https:\/\/doi.org\/10.1016\/j.eswa.2018.09.015","journal-title":"Expert Syst Appl"},{"key":"3378_CR9","doi-asserted-by":"publisher","first-page":"371","DOI":"10.1016\/j.neucom.2015.06.083","volume":"172","author":"E Emary","year":"2016","unstructured":"Emary E, Zawbaa HM, Hassanien AE (2016) Binary grey wolf optimization approaches for feature selection. Neurocomputing 172:371\u2013381. https:\/\/doi.org\/10.1016\/j.neucom.2015.06.083","journal-title":"Neurocomputing"},{"key":"3378_CR10","doi-asserted-by":"publisher","first-page":"130","DOI":"10.1016\/j.patrec.2013.01.026","volume":"35","author":"C De Stefano","year":"2014","unstructured":"De Stefano C, Fontanella F, Marrocco C, Scotto di Freca A (2014) A GA-based feature selection approach with an application to handwritten character recognition. Pattern Recognit Lett 35:130\u2013141. https:\/\/doi.org\/10.1016\/j.patrec.2013.01.026","journal-title":"Pattern Recognit Lett"},{"key":"3378_CR11","doi-asserted-by":"publisher","first-page":"1656","DOI":"10.1109\/TSMCB.2012.2227469","volume":"43","author":"B Xue","year":"2013","unstructured":"Xue B, Zhang M, Browne WN (2013) Particle swarm optimization for feature selection in classification: a multi-objective approach. IEEE Trans Cybern 43:1656\u20131671. https:\/\/doi.org\/10.1109\/TSMCB.2012.2227469","journal-title":"IEEE Trans Cybern"},{"key":"3378_CR12","doi-asserted-by":"publisher","first-page":"80","DOI":"10.1016\/j.advengsoft.2015.01.010","volume":"83","author":"S Mirjalili","year":"2015","unstructured":"Mirjalili S (2015) The ant lion optimizer. Adv Eng Softw 83:80\u201398. https:\/\/doi.org\/10.1016\/j.advengsoft.2015.01.010","journal-title":"Adv Eng Softw"},{"key":"3378_CR13","doi-asserted-by":"publisher","first-page":"216","DOI":"10.1016\/j.eswa.2017.04.017","volume":"82","author":"S Jiang","year":"2017","unstructured":"Jiang S, Chin K-S, Wang L et al (2017) Modified genetic algorithm-based feature selection combined with pre-trained deep neural network for demand forecasting in outpatient department. Expert Syst Appl 82:216\u2013230. https:\/\/doi.org\/10.1016\/j.eswa.2017.04.017","journal-title":"Expert Syst Appl"},{"key":"3378_CR14","doi-asserted-by":"publisher","first-page":"811","DOI":"10.1007\/s00500-016-2385-6","volume":"22","author":"S Gu","year":"2018","unstructured":"Gu S, Cheng R, Jin Y (2018) Feature selection for high-dimensional classification using a competitive swarm optimizer. Soft Comput 22:811\u2013822. https:\/\/doi.org\/10.1007\/s00500-016-2385-6","journal-title":"Soft Comput"},{"key":"3378_CR15","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1016\/j.patrec.2016.03.014","volume":"77","author":"S AbdEl-Fattah Sayed","year":"2016","unstructured":"AbdEl-Fattah Sayed S, Nabil E, Badr A (2016) A binary clonal flower pollination algorithm for feature selection. Pattern Recognit Lett 77:21\u201327. https:\/\/doi.org\/10.1016\/j.patrec.2016.03.014","journal-title":"Pattern Recognit Lett"},{"key":"3378_CR16","doi-asserted-by":"publisher","first-page":"1609","DOI":"10.1007\/s10489-017-0989-x","volume":"48","author":"A Adeli","year":"2018","unstructured":"Adeli A, Broumandnia A (2018) Image steganalysis using improved particle swarm optimization based feature selection. Appl Intell 48:1609\u20131622. https:\/\/doi.org\/10.1007\/s10489-017-0989-x","journal-title":"Appl Intell"},{"key":"3378_CR17","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.eswa.2017.04.019","volume":"83","author":"Y-P Chen","year":"2017","unstructured":"Chen Y-P, Li Y, Wang G et al (2017) A novel bacterial foraging optimization algorithm for feature selection. Expert Syst Appl 83:1\u201317. https:\/\/doi.org\/10.1016\/j.eswa.2017.04.019","journal-title":"Expert Syst Appl"},{"key":"3378_CR18","doi-asserted-by":"publisher","first-page":"31","DOI":"10.1016\/j.eswa.2015.12.004","volume":"49","author":"AS Ghareb","year":"2016","unstructured":"Ghareb AS, Bakar AA, Hamdan AR (2016) Hybrid feature selection based on enhanced genetic algorithm for text categorization. Expert Syst Appl 49:31\u201347. https:\/\/doi.org\/10.1016\/j.eswa.2015.12.004","journal-title":"Expert Syst Appl"},{"key":"3378_CR19","doi-asserted-by":"publisher","first-page":"334","DOI":"10.1016\/j.asoc.2015.07.023","volume":"36","author":"E Hancer","year":"2015","unstructured":"Hancer E, Xue B, Karaboga D, Zhang M (2015) A binary ABC algorithm based on advanced similarity scheme for feature selection. Appl Soft Comput 36:334\u2013348. https:\/\/doi.org\/10.1016\/j.asoc.2015.07.023","journal-title":"Appl Soft Comput"},{"key":"3378_CR20","doi-asserted-by":"publisher","first-page":"441","DOI":"10.1016\/j.asoc.2017.11.006","volume":"62","author":"M Mafarja","year":"2018","unstructured":"Mafarja M, Mirjalili S (2018) Whale optimization approaches for wrapper feature selection. Appl Soft Comput 62:441\u2013453. https:\/\/doi.org\/10.1016\/j.asoc.2017.11.006","journal-title":"Appl Soft Comput"},{"key":"3378_CR21","doi-asserted-by":"publisher","first-page":"2043","DOI":"10.1007\/s13042-017-0686-4","volume":"9","author":"M Mirhosseini","year":"2018","unstructured":"Mirhosseini M, Nezamabadi-pour H (2018) BICA: a binary imperialist competitive algorithm and its application in CBIR systems. Int J Mach Learn Cybern 9:2043\u20132057. https:\/\/doi.org\/10.1007\/s13042-017-0686-4","journal-title":"Int J Mach Learn Cybern"},{"key":"3378_CR22","doi-asserted-by":"publisher","first-page":"58","DOI":"10.3390\/computers7040058","volume":"7","author":"J Too","year":"2018","unstructured":"Too J, Abdullah AR, Mohd Saad N et al (2018) A new competitive binary grey wolf optimizer to solve the feature selection problem in EMG signals classification. Computers 7:58. https:\/\/doi.org\/10.3390\/computers7040058","journal-title":"Computers"},{"key":"3378_CR23","doi-asserted-by":"publisher","first-page":"205","DOI":"10.1007\/s10479-016-2331-0","volume":"265","author":"P Kr\u00f6mer","year":"2018","unstructured":"Kr\u00f6mer P, Plato\u0161 J, Nowakov\u00e1 J, Sn\u00e1\u0161el V (2018) Optimal column subset selection for image classification by genetic algorithms. Ann Oper Res 265:205\u2013222. https:\/\/doi.org\/10.1007\/s10479-016-2331-0","journal-title":"Ann Oper Res"},{"key":"3378_CR24","doi-asserted-by":"publisher","first-page":"65","DOI":"10.1007\/BF00175354","volume":"4","author":"D Whitley","year":"1994","unstructured":"Whitley D (1994) A genetic algorithm tutorial. Stat Comput 4:65\u201385. https:\/\/doi.org\/10.1007\/BF00175354","journal-title":"Stat Comput"},{"key":"3378_CR25","doi-asserted-by":"publisher","first-page":"231","DOI":"10.1016\/j.eswa.2005.09.024","volume":"31","author":"C-L Huang","year":"2006","unstructured":"Huang C-L, Wang C-J (2006) A GA-based feature selection and parameters optimization for support vector machines. Expert Syst Appl 31:231\u2013240. https:\/\/doi.org\/10.1016\/j.eswa.2005.09.024","journal-title":"Expert Syst Appl"},{"key":"3378_CR26","doi-asserted-by":"publisher","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. https:\/\/doi.org\/10.1109\/4235.585893","journal-title":"IEEE Trans Evol Comput"},{"key":"3378_CR27","doi-asserted-by":"publisher","first-page":"328","DOI":"10.1016\/j.asoc.2017.04.042","volume":"58","author":"B Ma","year":"2017","unstructured":"Ma B, Xia Y (2017) A tribe competition-based genetic algorithm for feature selection in pattern classification. Appl Soft Comput 58:328\u2013338. https:\/\/doi.org\/10.1016\/j.asoc.2017.04.042","journal-title":"Appl Soft Comput"},{"key":"3378_CR28","doi-asserted-by":"publisher","first-page":"575","DOI":"10.1016\/j.asoc.2018.11.012","volume":"75","author":"S Al-Sharhan","year":"2019","unstructured":"Al-Sharhan S, Bimba A (2019) Adaptive multi-parent crossover GA for feature optimization in epileptic seizure identification. Appl Soft Comput 75:575\u2013587. https:\/\/doi.org\/10.1016\/j.asoc.2018.11.012","journal-title":"Appl Soft Comput"},{"key":"3378_CR29","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1016\/j.asoc.2018.10.054","volume":"75","author":"D Jude Hemanth","year":"2019","unstructured":"Jude Hemanth D, Anitha J (2019) Modified genetic algorithm approaches for classification of abnormal magnetic resonance brain tumour images. Appl Soft Comput 75:21\u201328. https:\/\/doi.org\/10.1016\/j.asoc.2018.10.054","journal-title":"Appl Soft Comput"},{"key":"3378_CR30","unstructured":"UCI machine learning repository. https:\/\/archive.ics.uci.edu\/ml\/index.php. Accessed 24 Mar 2019"},{"key":"3378_CR31","unstructured":"Datasets|Feature selection @ ASU. http:\/\/featureselection.asu.edu\/datasets.php. Accessed 3 Oct 2019"},{"key":"3378_CR32","doi-asserted-by":"publisher","first-page":"561","DOI":"10.1016\/j.ins.2017.08.047","volume":"418\u2013419","author":"Y Zhang","year":"2017","unstructured":"Zhang Y, Song X, Gong D (2017) A return-cost-based binary firefly algorithm for feature selection. Inf Sci 418\u2013419:561\u2013574. https:\/\/doi.org\/10.1016\/j.ins.2017.08.047","journal-title":"Inf Sci"},{"key":"3378_CR33","doi-asserted-by":"publisher","first-page":"462","DOI":"10.1016\/j.ins.2017.09.028","volume":"422","author":"E Hancer","year":"2018","unstructured":"Hancer E, Xue B, Zhang M et al (2018) Pareto front feature selection based on artificial bee colony optimization. Inf Sci 422:462\u2013479. https:\/\/doi.org\/10.1016\/j.ins.2017.09.028","journal-title":"Inf Sci"},{"key":"3378_CR34","doi-asserted-by":"publisher","first-page":"2795","DOI":"10.1007\/s00521-016-2204-0","volume":"28","author":"L Zhang","year":"2017","unstructured":"Zhang L, Shan L, Wang J (2017) Optimal feature selection using distance-based discrete firefly algorithm with mutual information criterion. Neural Comput Appl 28:2795\u20132808. https:\/\/doi.org\/10.1007\/s00521-016-2204-0","journal-title":"Neural Comput Appl"},{"key":"3378_CR35","doi-asserted-by":"publisher","first-page":"992","DOI":"10.1016\/j.ress.2005.11.018","volume":"91","author":"A Konak","year":"2006","unstructured":"Konak A, Coit DW, Smith AE (2006) Multi-objective optimization using genetic algorithms: a tutorial. Reliab Eng Syst Saf 91:992\u20131007. https:\/\/doi.org\/10.1016\/j.ress.2005.11.018","journal-title":"Reliab Eng Syst Saf"},{"key":"3378_CR36","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.jss.2016.07.006","volume":"124","author":"B Keshanchi","year":"2017","unstructured":"Keshanchi B, Souri A, Navimipour NJ (2017) An improved genetic algorithm for task scheduling in the cloud environments using the priority queues: formal verification, simulation, and statistical testing. J Syst Softw 124:1\u201321. https:\/\/doi.org\/10.1016\/j.jss.2016.07.006","journal-title":"J Syst Softw"},{"key":"3378_CR37","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\u201373","journal-title":"Sci Am"},{"key":"3378_CR38","doi-asserted-by":"publisher","first-page":"191","DOI":"10.1109\/TCYB.2014.2322602","volume":"45","author":"R Cheng","year":"2015","unstructured":"Cheng R, Jin Y (2015) A competitive swarm optimizer for large scale optimization. IEEE Trans Cybern 45:191\u2013204. https:\/\/doi.org\/10.1109\/TCYB.2014.2322602","journal-title":"IEEE Trans Cybern"},{"key":"3378_CR39","doi-asserted-by":"publisher","first-page":"134","DOI":"10.1016\/j.eswa.2018.03.024","volume":"104","author":"M Eshtay","year":"2018","unstructured":"Eshtay M, Faris H, Obeid N (2018) Improving extreme learning machine by competitive swarm optimization and its application for medical diagnosis problems. Expert Syst Appl 104:134\u2013152. https:\/\/doi.org\/10.1016\/j.eswa.2018.03.024","journal-title":"Expert Syst Appl"},{"key":"3378_CR40","doi-asserted-by":"publisher","first-page":"113364","DOI":"10.1016\/j.eswa.2020.113364","volume":"152","author":"N Neggaz","year":"2020","unstructured":"Neggaz N, Houssein EH, Hussain K (2020) An efficient henry gas solubility optimization for feature selection. Expert Syst Appl 152:113364. https:\/\/doi.org\/10.1016\/j.eswa.2020.113364","journal-title":"Expert Syst Appl"},{"key":"3378_CR41","doi-asserted-by":"publisher","first-page":"412","DOI":"10.1016\/j.compeleceng.2018.04.014","volume":"68","author":"D Gupta","year":"2018","unstructured":"Gupta D, Sundaram S, Khanna A et al (2018) Improved diagnosis of Parkinson\u2019s disease using optimized crow search algorithm. Comput Electr Eng 68:412\u2013424. https:\/\/doi.org\/10.1016\/j.compeleceng.2018.04.014","journal-title":"Comput Electr Eng"},{"key":"3378_CR42","doi-asserted-by":"publisher","first-page":"29","DOI":"10.1016\/j.compbiolchem.2007.09.005","volume":"32","author":"L-Y Chuang","year":"2008","unstructured":"Chuang L-Y, Chang H-W, Tu C-J, Yang C-H (2008) Improved binary PSO for feature selection using gene expression data. Comput Biol Chem 32:29\u201338. https:\/\/doi.org\/10.1016\/j.compbiolchem.2007.09.005","journal-title":"Comput Biol Chem"},{"key":"3378_CR43","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. https:\/\/doi.org\/10.1007\/s10898-007-9149-x","journal-title":"J Glob Optim"}],"container-title":["The Journal of Supercomputing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11227-020-03378-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11227-020-03378-9\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11227-020-03378-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,7,5]],"date-time":"2021-07-05T23:53:28Z","timestamp":1625529208000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11227-020-03378-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,7,6]]},"references-count":43,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2021,3]]}},"alternative-id":["3378"],"URL":"https:\/\/doi.org\/10.1007\/s11227-020-03378-9","relation":{},"ISSN":["0920-8542","1573-0484"],"issn-type":[{"value":"0920-8542","type":"print"},{"value":"1573-0484","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,7,6]]},"assertion":[{"value":"6 July 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":"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"}}]}}