{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,5]],"date-time":"2026-03-05T02:09:05Z","timestamp":1772676545710,"version":"3.50.1"},"reference-count":43,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2025,8,28]],"date-time":"2025-08-28T00:00:00Z","timestamp":1756339200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,8,28]],"date-time":"2025-08-28T00:00:00Z","timestamp":1756339200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Memetic Comp."],"published-print":{"date-parts":[[2025,9]]},"DOI":"10.1007\/s12293-025-00478-y","type":"journal-article","created":{"date-parts":[[2025,8,28]],"date-time":"2025-08-28T11:22:05Z","timestamp":1756380125000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Ensemble of simple optimizers"],"prefix":"10.1007","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4695-6919","authenticated-orcid":false,"given":"Mahamed G. H.","family":"Omran","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ayed","family":"Salman","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Maurice","family":"Clerc","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,8,28]]},"reference":[{"key":"478_CR1","doi-asserted-by":"publisher","first-page":"304","DOI":"10.1016\/j.asoc.2015.04.019","volume":"33","author":"MZ Ali","year":"2015","unstructured":"Ali MZ, Awad NH, Suganthan PN (2015) Multi-population differential evolution with balanced ensemble of mutation strategies for large-scale global optimization. Appl Soft Comput 33:304\u2013327","journal-title":"Appl Soft Comput"},{"issue":"1","key":"478_CR2","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s11721-021-00202-9","volume":"16","author":"C Aranha","year":"2022","unstructured":"Aranha C, CamachoVillal\u00f3n CL, Campelo F, Dorigo M, Ruiz R, Sevaux M, S\u00f6rensen K, St\u00fctzle T (2022) Metaphor-based metaheuristics, a call for action: the elephant in the room. Swarm Intell 16(1):1\u20136","journal-title":"Swarm Intell"},{"key":"478_CR3","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2022.105622","volume":"117","author":"A Alorf","year":"2023","unstructured":"Alorf A (2023) A survey of recently developed metaheuristics and their comparative analysis. Eng Appl Artif Intell 117:105622","journal-title":"Eng Appl Artif Intell"},{"key":"478_CR4","doi-asserted-by":"crossref","unstructured":"Clerc M (2015) Guided Randomness in Optimization. Wiley,","DOI":"10.1002\/9781119136439"},{"key":"478_CR5","doi-asserted-by":"crossref","unstructured":"Clerc M (2019) Difficulty Measures and Benchmarks for Iterative Optimisers. Wiley,","DOI":"10.1002\/9781119612476"},{"key":"478_CR6","unstructured":"Das S, Suganthan P (2010) Problem definitions and evaluation criteria for CEC 2011 competition on testing evolutionary algorithms on real world optimization problems. Technical report, Jadavpur University, Nanyang Technological University,"},{"key":"478_CR7","doi-asserted-by":"publisher","DOI":"10.1016\/j.cie.2019.106040","volume":"137","author":"T Dokeroglu","year":"2019","unstructured":"Dokeroglu T, Sevinc E, Kucukyilmaz T, Cosar A (2019) A survey on new generation metaheuristic algorithms. Computers & Industrial Engineering 137:106040","journal-title":"Computers & Industrial Engineering"},{"key":"478_CR8","doi-asserted-by":"publisher","first-page":"4329","DOI":"10.1007\/s10462-022-10234-0","volume":"56","author":"L da Silva","year":"2023","unstructured":"da Silva L, L\u00facio Y, Coelho L (2023) A comprehensive review on jaya optimization algorithm. Artif Intell Rev 56:4329\u20134361","journal-title":"Artif Intell Rev"},{"issue":"5","key":"478_CR9","doi-asserted-by":"publisher","first-page":"4329","DOI":"10.1007\/s10462-022-10234-0","volume":"56","author":"L ScapinelloAquinodaSilva","year":"2023","unstructured":"ScapinelloAquinodaSilva L, LievenSouzaL\u00facio Y, SantosCoelho L, Mariani VC, Rao RV (2023) A comprehensive review on Jaya optimization algorithm. Artif Intell Rev 56(5):4329\u20134361","journal-title":"Artif Intell Rev"},{"key":"478_CR10","doi-asserted-by":"crossref","unstructured":"Elsayed SM, Sarker RA, Essam DL (2011) GA with a new multi-parent crossover for solving IEEE-CEC2011 competition problems. In Congress on Evolutionary Computation (CEC), pages 1034\u20131040. IEEE,","DOI":"10.1109\/CEC.2011.5949731"},{"key":"478_CR11","doi-asserted-by":"crossref","unstructured":"Glover F, Laguna M (1998) Tabu Search, pages 2093\u20132229. Springer US, Boston, MA,","DOI":"10.1007\/978-1-4613-0303-9_33"},{"key":"478_CR12","volume-title":"Genetic Algorithms in Search, Optimization, and Machine Learning","author":"DE Goldberg","year":"1989","unstructured":"Goldberg DE (1989) Genetic Algorithms in Search, Optimization, and Machine Learning. Addison-Wesley, New York"},{"key":"478_CR13","doi-asserted-by":"publisher","first-page":"84","DOI":"10.1016\/j.matcom.2021.08.013","volume":"192","author":"FA Hashim","year":"2022","unstructured":"Hashim FA, Houssein EH, Hussain K, Mabrouk MS, Al-Atabany W (2022) Honey badger algorithm: New metaheuristic algorithm for solving optimization problems. Math Comput Simul 192:84\u2013110","journal-title":"Math Comput Simul"},{"key":"478_CR14","doi-asserted-by":"crossref","unstructured":"Iacca G, Caraffini F, Neri F (2015) Continuous parameter pools in ensemble differential evolution. In IEEE Symposium Series on Computational Intelligence (SSCI). IEEE,","DOI":"10.1109\/SSCI.2015.216"},{"key":"478_CR15","doi-asserted-by":"crossref","unstructured":"Iacca G, Neri F, Caraffini F, Suganthan PN (2014) A differential evolution framework with ensemble of parameters and strategies and pool of local search algorithms. In Applications of Evolutionary Computation (EvoStar\/EvoApps). Springer,","DOI":"10.1007\/978-3-662-45523-4_50"},{"key":"478_CR16","doi-asserted-by":"crossref","unstructured":"Kennedy J, Eberhart R (1995) Particle swarm optimization. In International Joint Conference on Neural Networks (IJCNN), pages 1942\u20131948. IEEE,","DOI":"10.1109\/ICNN.1995.488968"},{"key":"478_CR17","doi-asserted-by":"crossref","unstructured":"Kirkpatrick S, Gelatt CD, Vecchi MP Optimization by simulated annealing. Science, 220:671\u2013680, 4598","DOI":"10.1126\/science.220.4598.671"},{"key":"478_CR18","doi-asserted-by":"publisher","first-page":"155","DOI":"10.1007\/s12293-022-00386-5","volume":"15","author":"GS Khalfi","year":"2023","unstructured":"Khalfi GS, Iacca G, Draa A (2023) A single-solution\u2013compact hybrid algorithm for continuous optimization. Memetic Computing 15:155\u2013204","journal-title":"Memetic Computing"},{"key":"478_CR19","doi-asserted-by":"publisher","first-page":"11999","DOI":"10.1007\/s00521-019-04179-9","volume":"32","author":"P Kopciewicz","year":"2020","unstructured":"Kopciewicz P, Lukasik S (2020) Exploiting flower constancy in flower pollination algorithm: improved biotic flower pollination algorithm and its experimental evaluation. Neural Comput Appl 32:11999\u201312010","journal-title":"Neural Comput Appl"},{"key":"478_CR20","unstructured":"Liang J, Qu B, Suganthan P, Hernandez-Diaz A (2013) Problem definitions and evaluation criteria for the CEC 2013 special session on real-parameter optimization. Technical report, Zhengzhou University,Nanyang Technological University,"},{"issue":"3","key":"478_CR21","doi-asserted-by":"publisher","first-page":"2835","DOI":"10.32604\/cmc.2023.038670","volume":"76","author":"H Li","year":"2023","unstructured":"Li H, Tang J, Pan Q, Zhan J, Lao S (2023) Ensemble of population-based metaheuristic algorithms. Computers Materials & Continua 76(3):2835\u20132859","journal-title":"Computers Materials & Continua"},{"key":"478_CR22","unstructured":"Mikolov T, Chen K, Corrado G, Dean J (2013) Efficient estimation of word representations in vector space,"},{"key":"478_CR23","unstructured":"Di Caro M Dorigo G (1999) The ant colony optimization meta-heuristic. In F.\u00a0Glover D.\u00a0Corne, M.\u00a0Dorigo, editor, New Ideas in Optimization, pages 11\u201332. McGraw Hill, London,"},{"issue":"5","key":"478_CR24","doi-asserted-by":"publisher","first-page":"1120","DOI":"10.1109\/TEVC.2009.2021465","volume":"13","author":"MA MontesdeOca","year":"2009","unstructured":"MontesdeOca MA, St\u00fctzle T, Birattari M, Dorigo M (2009) Frankenstein\u2019s pso: A composite particle swarm optimization algorithm. IEEE Trans Evol Comput 13(5):1120\u20131132","journal-title":"IEEE Trans Evol Comput"},{"issue":"11","key":"478_CR25","doi-asserted-by":"publisher","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. Computers & Operations Research 24(11):1097\u20131100","journal-title":"Computers & Operations Research"},{"key":"478_CR26","doi-asserted-by":"publisher","first-page":"176","DOI":"10.1016\/j.ins.2021.11.076","volume":"586","author":"Z Meng","year":"2022","unstructured":"Meng Z, Zhong Y, Mao G, Liang Y (2022) PSO-sono: A novel PSO variant for single-objective numerical optimization. Inf Sci 586:176\u2013191","journal-title":"Inf Sci"},{"key":"478_CR27","doi-asserted-by":"publisher","first-page":"37","DOI":"10.1016\/j.knosys.2019.01.018","volume":"171","author":"P Niu","year":"2019","unstructured":"Niu P, Niu S, liu N, Chang L (2019) The defect of the grey wolf optimization algorithm and its verification method. Knowl-Based Syst 171:37\u201343","journal-title":"Knowl-Based Syst"},{"key":"478_CR28","doi-asserted-by":"crossref","unstructured":"Omran M, Clerc M, Ghaddar F, Aldabagh A, Tawfik O (2022) Permutation tests for metaheuristic algorithms Mathematics 10(13):","DOI":"10.3390\/math10132219"},{"issue":"1","key":"478_CR29","first-page":"1178","volume":"31","author":"M Omran","year":"2022","unstructured":"Omran M, Iacca G (2022) An improved Jaya optimization algorithm with ring topology and population size reduction. J Intell Syst 31(1):1178\u20131210","journal-title":"J Intell Syst"},{"key":"478_CR30","doi-asserted-by":"crossref","unstructured":"Pierezan J, Dos SantosCoelho L (2018) Coyote optimization algorithm: A new metaheuristic for global optimization problems. In 2018 IEEE Congress on Evolutionary Computation (CEC), pages 1\u20138,","DOI":"10.1109\/CEC.2018.8477769"},{"key":"478_CR31","doi-asserted-by":"crossref","unstructured":"Pol\u00e1kov\u00e1 R, Tvrdik J, Bujok P (2017) Adaptation of population size according to current population diversity in differential evolution. In In Proceedings of the IEEE 2017 Symposium Series on Computational Intelligence (SSCI), pages 2627\u20132634. IEEE,","DOI":"10.1109\/SSCI.2017.8280914"},{"issue":"1","key":"478_CR32","first-page":"19","volume":"7","author":"RV Rao","year":"2016","unstructured":"Rao RV (2016) Jaya: A simple and new optimization algorithm for solving constrained and unconstrained optimization problems. Int J Ind Eng Comput 7(1):19\u201334","journal-title":"Int J Ind Eng Comput"},{"issue":"1","key":"478_CR33","first-page":"107","volume":"11","author":"R Rao","year":"2020","unstructured":"Rao R (2020) Rao algorithms: Three metaphor-less simple algorithms for solving optimization problems. Int J Ind Eng Comput 11(1):107\u2013130","journal-title":"Int J Ind Eng Comput"},{"issue":"7","key":"478_CR34","doi-asserted-by":"publisher","first-page":"3847","DOI":"10.1007\/s00500-022-07589-5","volume":"27","author":"RV Rao","year":"2022","unstructured":"Rao RV, Pawar RB (2022) Improved Rao algorithm: a simple and effective algorithm for constrained mechanical design optimization problems. Soft Comput 27(7):3847\u20133868","journal-title":"Soft Comput"},{"key":"478_CR35","volume-title":"Evolution and Optimum Seeking: The Sixth Generation","author":"Hans-Paul Paul Schwefel","year":"1993","unstructured":"Hans-Paul Paul Schwefel (1993) Evolution and Optimum Seeking: The Sixth Generation. John Wiley & Sons Inc, USA"},{"key":"478_CR36","doi-asserted-by":"publisher","DOI":"10.1016\/j.cie.2021.107739","volume":"162","author":"P Singh","year":"2021","unstructured":"Singh P, Kottath R (2021) An ensemble approach to meta-heuristic algorithms: Comparative analysis and its applications. Computers & Industrial Engineering 162:107739","journal-title":"Computers & Industrial Engineering"},{"key":"478_CR37","volume-title":"Differential evolution-a simple and efficient adaptive scheme for global optimization over continuous spaces","author":"R Storn","year":"1995","unstructured":"Storn R, Price K (1995) Differential evolution-a simple and efficient adaptive scheme for global optimization over continuous spaces. ICSI, Technical report, Berkeley"},{"key":"478_CR38","doi-asserted-by":"publisher","first-page":"183","DOI":"10.1016\/j.neucom.2023.02.010","volume":"532","author":"S Hang","year":"2023","unstructured":"Hang S, Zhao D, Heidari AA, Liu L, Zhang X, Mafarja M, Chen H (2023) Rime: A physics-based optimization. Neurocomputing 532:183\u2013214","journal-title":"Neurocomputing"},{"key":"478_CR39","doi-asserted-by":"crossref","unstructured":"Tanabe R, Fukunaga A (2014) Improving the search performance of SHADE using linear population size reduction. In Congress on Evolutionary Computation (CEC), pages 1658\u20131665. IEEE,","DOI":"10.1109\/CEC.2014.6900380"},{"issue":"2","key":"478_CR40","doi-asserted-by":"publisher","first-page":"243","DOI":"10.1109\/TEVC.2008.924428","volume":"13","author":"JA Vrugt","year":"2009","unstructured":"Vrugt JA, Robinson BA, Hyman JM (2009) Self-adaptive multimethod search for global optimization in real-parameter spaces. IEEE Trans Evol Comput 13(2):243\u2013259","journal-title":"IEEE Trans Evol Comput"},{"issue":"3","key":"478_CR41","first-page":"722","volume":"106","author":"JA Vrugt","year":"2009","unstructured":"Vrugt JA, Robinson BA, TerBraak CJF (2009) Improved evolutionary optimization from genetically adaptive multimethod search. Proc Natl Acad Sci 106(3):722\u2013727","journal-title":"Proc Natl Acad Sci"},{"key":"478_CR42","doi-asserted-by":"publisher","first-page":"695","DOI":"10.1016\/j.swevo.2018.08.015","volume":"44","author":"W Guohua","year":"2019","unstructured":"Guohua W, Mallipeddi R, Suganthan PN (2019) Ensemble strategies for population-based optimization algorithms - a survey. Swarm Evol Comput 44:695-711","journal-title":"Swarm Evol Comput"},{"key":"478_CR43","doi-asserted-by":"crossref","unstructured":"Yang XS (2012) Flower pollination algorithm for global optimization. In J\u00e9r\u00f4me Durand-Lose and Nata\u0161a Jonoska, editors, Unconventional Computation and Natural Computation, pages 240\u2013249, Berlin, Heidelberg, Springer Berlin Heidelberg","DOI":"10.1007\/978-3-642-32894-7_27"}],"container-title":["Memetic Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12293-025-00478-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s12293-025-00478-y\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12293-025-00478-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,11]],"date-time":"2025-09-11T06:54:49Z","timestamp":1757573689000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s12293-025-00478-y"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8,28]]},"references-count":43,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2025,9]]}},"alternative-id":["478"],"URL":"https:\/\/doi.org\/10.1007\/s12293-025-00478-y","relation":{},"ISSN":["1865-9284","1865-9292"],"issn-type":[{"value":"1865-9284","type":"print"},{"value":"1865-9292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,8,28]]},"assertion":[{"value":"12 September 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 August 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"28 August 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing Interests"}},{"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 and informed consent for data used"}}],"article-number":"41"}}