{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T14:55:30Z","timestamp":1777388130669,"version":"3.51.4"},"reference-count":96,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,8,19]],"date-time":"2025-08-19T00:00:00Z","timestamp":1755561600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2025,8,19]],"date-time":"2025-08-19T00:00:00Z","timestamp":1755561600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Big Data"],"DOI":"10.1186\/s40537-025-01260-0","type":"journal-article","created":{"date-parts":[[2025,8,19]],"date-time":"2025-08-19T11:36:39Z","timestamp":1755603399000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["IECO: an improved educational competition optimizer for state-of-the-art engineering optimization"],"prefix":"10.1186","volume":"12","author":[{"given":"Xiaojie","family":"Tang","sequence":"first","affiliation":[]},{"given":"Junbo Jacob","family":"Lian","sequence":"additional","affiliation":[]},{"given":"Ling","family":"Ma","sequence":"additional","affiliation":[]},{"given":"Xincan","family":"Wu","sequence":"additional","affiliation":[]},{"given":"Rui","family":"Zhong","sequence":"additional","affiliation":[]},{"given":"Yujun","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Huiling","family":"Chen","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,8,19]]},"reference":[{"key":"1260_CR1","first-page":"1","volume":"2023","author":"X Shen","year":"2023","unstructured":"Shen X, Du S-C, Sun Y-N, Sun PZ, Law R, Wu EQ. Advance scheduling for chronic care under online or offline revisit uncertainty. IEEE Trans Autom Sci Eng. 2023;2023:1.","journal-title":"IEEE Trans Autom Sci Eng"},{"issue":"1","key":"1260_CR2","doi-asserted-by":"publisher","first-page":"174","DOI":"10.1190\/1.1444893","volume":"66","author":"W Rodi","year":"2001","unstructured":"Rodi W, Mackie RL. Nonlinear conjugate gradients algorithm for 2-D magnetotelluric inversion. Geophysics. 2001;66(1):174\u201387.","journal-title":"Geophysics"},{"issue":"2","key":"1260_CR3","doi-asserted-by":"publisher","first-page":"890","DOI":"10.1137\/080714488","volume":"31","author":"E Van Den Berg","year":"2009","unstructured":"Van Den Berg E, Friedlander MP. Probing the Pareto frontier for basis pursuit solutions. SIAM J Sci Comput. 2009;31(2):890\u2013912.","journal-title":"SIAM J Sci Comput"},{"issue":"5786","key":"1260_CR4","doi-asserted-by":"publisher","first-page":"504","DOI":"10.1126\/science.1127647","volume":"313","author":"GE Hinton","year":"2006","unstructured":"Hinton GE, Salakhutdinov RR. Reducing the dimensionality of data with neural networks. Science. 2006;313(5786):504\u20137.","journal-title":"Science"},{"issue":"6","key":"1260_CR5","doi-asserted-by":"publisher","first-page":"3841","DOI":"10.1109\/TITS.2021.3059455","volume":"22","author":"B Cao","year":"2021","unstructured":"Cao B, et al. Large-scale many-objective deployment optimization of edge servers. IEEE Trans Intell Transp Syst. 2021;22(6):3841\u20139.","journal-title":"IEEE Trans Intell Transp Syst"},{"issue":"4","key":"1260_CR6","doi-asserted-by":"publisher","first-page":"2133","DOI":"10.1109\/TITS.2020.3040909","volume":"22","author":"B Cao","year":"2020","unstructured":"Cao B, Zhao J, Lv Z, Yang P. Diversified personalized recommendation optimization based on mobile data. IEEE Trans Intell Transp Syst. 2020;22(4):2133\u20139.","journal-title":"IEEE Trans Intell Transp Syst"},{"key":"1260_CR7","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2021.107529","volume":"233","author":"R Dong","year":"2021","unstructured":"Dong R, Chen H, Heidari AA, Turabieh H, Mafarja M, Wang S. Boosted kernel search: framework, analysis and case studies on the economic emission dispatch problem. Knowl-Based Syst. 2021;233: 107529.","journal-title":"Knowl-Based Syst"},{"issue":"1","key":"1260_CR8","doi-asserted-by":"publisher","first-page":"013047","DOI":"10.1117\/1.JEI.32.1.013047","volume":"32","author":"T Guo","year":"2023","unstructured":"Guo T, Yuan H, Wang L, Wang T. Rate-distortion optimized quantization for geometry-based point cloud compression. J Electron Imaging. 2023;32(1):013047\u2013013047.","journal-title":"J Electron Imaging"},{"key":"1260_CR9","doi-asserted-by":"publisher","first-page":"195","DOI":"10.1016\/j.neucom.2018.09.001","volume":"320","author":"N Zeng","year":"2018","unstructured":"Zeng N, Qiu H, Wang Z, Liu W, Zhang H, Li Y. A new switching-delayed-PSO-based optimized SVM algorithm for diagnosis of Alzheimer\u2019s disease. Neurocomputing. 2018;320:195\u2013202.","journal-title":"Neurocomputing"},{"issue":"9","key":"1260_CR10","doi-asserted-by":"publisher","first-page":"9290","DOI":"10.1109\/TCYB.2020.3029748","volume":"52","author":"N Zeng","year":"2020","unstructured":"Zeng N, Wang Z, Liu W, Zhang H, Hone K, Liu X. A dynamic neighborhood-based switching particle swarm optimization algorithm. IEEE Trans Cybern. 2020;52(9):9290\u2013301.","journal-title":"IEEE Trans Cybern"},{"key":"1260_CR11","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2021.115079","volume":"181","author":"I Ahmadianfar","year":"2021","unstructured":"Ahmadianfar I, Heidari AA, Gandomi AH, Chu X, Chen H. Run beyond the metaphor: an efficient optimization algorithm based on Runge Kutta method. Expert Syst Appl. 2021;181: 115079.","journal-title":"Expert Syst Appl"},{"key":"1260_CR12","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2022.116516","volume":"195","author":"I Ahmadianfar","year":"2022","unstructured":"Ahmadianfar I, Heidari AA, Noshadian S, Chen H, Gandomi AH. Info: an efficient optimization algorithm based on weighted mean of vectors. Expert Syst Appl. 2022;195: 116516.","journal-title":"Expert Syst Appl"},{"key":"1260_CR13","doi-asserted-by":"publisher","DOI":"10.1109\/TIE.2023.3321997","author":"C Zhang","year":"2023","unstructured":"Zhang C, Zhou L, Li Y. Pareto optimal reconfiguration planning and distributed parallel motion control of mobile modular robots. IEEE Trans Ind Electr. 2023. https:\/\/doi.org\/10.1109\/TIE.2023.3321997.","journal-title":"IEEE Trans Ind Electr"},{"key":"1260_CR14","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2022.105810","volume":"148","author":"A Qi","year":"2022","unstructured":"Qi A, et al. Directional mutation and crossover boosted ant colony optimization with application to COVID-19 X-ray image segmentation. Comput Biol Med. 2022;148: 105810.","journal-title":"Comput Biol Med"},{"key":"1260_CR15","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2021.105137","volume":"141","author":"J Xia","year":"2022","unstructured":"Xia J, et al. Evolving kernel extreme learning machine for medical diagnosis via a disperse foraging sine cosine algorithm. Comput Biol Med. 2022;141: 105137.","journal-title":"Comput Biol Med"},{"key":"1260_CR16","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2022.104836","volume":"112","author":"K Tafakkori","year":"2022","unstructured":"Tafakkori K, Tavakkoli-Moghaddam R, Siadat A. Sustainable negotiation-based nesting and scheduling in additive manufacturing systems: a case study and multi-objective meta-heuristic algorithms. Eng Appl Artif Intell. 2022;112: 104836.","journal-title":"Eng Appl Artif Intell"},{"issue":"1","key":"1260_CR17","doi-asserted-by":"publisher","first-page":"1566","DOI":"10.1080\/10942912.2023.2221404","volume":"26","author":"J Lian","year":"2023","unstructured":"Lian J, et al. Visualized pattern recognition optimization for apple mechanical damage by laser relaxation spectroscopy. Int J Food Prop. 2023;26(1):1566\u201378.","journal-title":"Int J Food Prop"},{"key":"1260_CR18","doi-asserted-by":"crossref","unstructured":"Zhou W, Lian J, Zhang J, Mei Z, Gao Y, Hui G. Tomato storage quality predicting method based on portable electronic nose system combined with WOA-SVM model. J Food Meas Characteri. 2023;17:1\u201311","DOI":"10.1007\/s11694-023-01865-0"},{"issue":"9","key":"1260_CR19","doi-asserted-by":"publisher","first-page":"4303","DOI":"10.1007\/s00500-022-06834-1","volume":"26","author":"G Divsalar","year":"2022","unstructured":"Divsalar G, Divsalar A, Jabbarzadeh A, Sahebi H. An optimization approach for green tourist trip design. Soft Comput. 2022;26(9):4303\u201332.","journal-title":"Soft Comput"},{"issue":"2","key":"1260_CR20","doi-asserted-by":"publisher","first-page":"144","DOI":"10.1016\/j.jocs.2013.12.001","volume":"5","author":"V Kumar","year":"2014","unstructured":"Kumar V, Chhabra JK, Kumar D. Parameter adaptive harmony search algorithm for unimodal and multimodal optimization problems. J Comput Sci. 2014;5(2):144\u201355.","journal-title":"J Comput Sci"},{"key":"1260_CR21","doi-asserted-by":"publisher","DOI":"10.1016\/j.cma.2020.113017","volume":"366","author":"C Wang","year":"2020","unstructured":"Wang C, Koh JM, Yu T, Xie NG, Cheong KH. Material and shape optimization of bi-directional functionally graded plates by GIGA and an improved multi-objective particle swarm optimization algorithm. Comput Methods Appl Mech Eng. 2020;366: 113017.","journal-title":"Comput Methods Appl Mech Eng"},{"key":"1260_CR22","doi-asserted-by":"publisher","first-page":"341","DOI":"10.1016\/j.cma.2018.04.037","volume":"339","author":"W Zhao","year":"2018","unstructured":"Zhao W, Du C, Jiang S. An adaptive multiscale approach for identifying multiple flaws based on XFEM and a discrete artificial fish swarm algorithm. Comput Methods Appl Mech Eng. 2018;339:341\u201357.","journal-title":"Comput Methods Appl Mech Eng"},{"issue":"1","key":"1260_CR23","doi-asserted-by":"publisher","first-page":"204","DOI":"10.1080\/00207721.2022.2153635","volume":"54","author":"H Chen","year":"2023","unstructured":"Chen H, Li C, Mafarja M, Heidari AA, Chen Y, Cai Z. Slime mould algorithm: a comprehensive review of recent variants and applications. Int J Syst Sci. 2023;54(1):204\u201335.","journal-title":"Int J Syst Sci"},{"key":"1260_CR24","doi-asserted-by":"publisher","first-page":"356","DOI":"10.1016\/j.neucom.2022.04.117","volume":"494","author":"H Li","year":"2022","unstructured":"Li H, Li J, Wu P, You Y, Zeng N. A ranking-system-based switching particle swarm optimizer with dynamic learning strategies. Neurocomputing. 2022;494:356\u201367.","journal-title":"Neurocomputing"},{"key":"1260_CR25","doi-asserted-by":"crossref","unstructured":"Burke EK, Burke EK, Kendall G, Kendall G. Search methodologies: introductory tutorials in optimization and decision support techniques. Springer. 2014.","DOI":"10.1007\/978-1-4614-6940-7"},{"key":"1260_CR26","doi-asserted-by":"publisher","first-page":"341","DOI":"10.1023\/A:1008202821328","volume":"11","author":"R Storn","year":"1997","unstructured":"Storn R, Price K. Differential evolution\u2013a simple and efficient heuristic for global optimization over continuous spaces. J Glob Optim. 1997;11:341\u201359.","journal-title":"J Glob Optim"},{"key":"1260_CR27","doi-asserted-by":"crossref","unstructured":"Kennedy J, Eberhart R. Particle swarm optimization. In: Proceedings of ICNN'95-international conference on neural networks, vol. 4. 1995. pp. 1942\u20131948.","DOI":"10.1109\/ICNN.1995.488968"},{"key":"1260_CR28","first-page":"6599","volume":"22","author":"Z Xiao","year":"2022","unstructured":"Xiao Z, et al. Multi-objective parallel task offloading and content caching in D2D-aided MEC networks. IEEE Trans Mob Comput. 2022;22:6599\u2013615.","journal-title":"IEEE Trans Mob Comput"},{"key":"1260_CR29","doi-asserted-by":"publisher","first-page":"300","DOI":"10.1016\/j.future.2020.03.055","volume":"111","author":"S Li","year":"2020","unstructured":"Li S, Chen H, Wang M, Heidari AA, Mirjalili S. Slime mould algorithm: a new method for stochastic optimization. Future Gener Comput Syst. 2020;111:300\u201323.","journal-title":"Future Gener Comput Syst"},{"key":"1260_CR30","doi-asserted-by":"publisher","first-page":"849","DOI":"10.1016\/j.future.2019.02.028","volume":"97","author":"AA Heidari","year":"2019","unstructured":"Heidari AA, Mirjalili S, Faris H, Aljarah I, Mafarja M, Chen H. Harris hawks optimization: algorithm and applications. Future Gener Comput Syst. 2019;97:849\u201372.","journal-title":"Future Gener Comput Syst"},{"key":"1260_CR31","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2024.108064","volume":"172","author":"J Lian","year":"2024","unstructured":"Lian J, et al. Parrot optimizer: algorithm and applications to medical problems. Comput Biol Med. 2024;172: 108064.","journal-title":"Comput Biol Med"},{"issue":"4","key":"1260_CR32","doi-asserted-by":"publisher","first-page":"353","DOI":"10.1016\/j.plrev.2005.10.001","volume":"2","author":"C Blum","year":"2005","unstructured":"Blum C. Ant colony optimization: introduction and recent trends. Phys Life Rev. 2005;2(4):353\u201373.","journal-title":"Phys Life Rev"},{"issue":"4","key":"1260_CR33","doi-asserted-by":"publisher","first-page":"28","DOI":"10.1109\/MCI.2006.329691","volume":"1","author":"M Dorigo","year":"2006","unstructured":"Dorigo M, Birattari M, Stutzle T. Ant colony optimization. IEEE Comput Intell Mag. 2006;1(4):28\u201339.","journal-title":"IEEE Comput Intell Mag"},{"issue":"5","key":"1260_CR34","doi-asserted-by":"publisher","first-page":"464","DOI":"10.1108\/02644401211235834","volume":"29","author":"XS Yang","year":"2012","unstructured":"Yang XS, Hossein Gandomi A. Bat algorithm: a novel approach for global engineering optimization. Eng Comput. 2012;29(5):464\u201383.","journal-title":"Eng Comput"},{"key":"1260_CR35","doi-asserted-by":"publisher","first-page":"183","DOI":"10.1016\/j.neucom.2023.02.010","volume":"532","author":"H Su","year":"2023","unstructured":"Su H, et al. RIME: A physics-based optimization. Neurocomputing. 2023;532:183\u2013214.","journal-title":"Neurocomputing"},{"key":"1260_CR36","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2024.128427","volume":"607","author":"C Yuan","year":"2024","unstructured":"Yuan C, Zhao D, Heidari AA, Liu L, Chen Y, Chen H. Polar lights optimizer: algorithm and applications in image segmentation and feature selection. Neurocomputing. 2024;607: 128427.","journal-title":"Neurocomputing"},{"key":"1260_CR37","doi-asserted-by":"publisher","first-page":"495","DOI":"10.1007\/s00521-015-1870-7","volume":"27","author":"S Mirjalili","year":"2016","unstructured":"Mirjalili S, Mirjalili SM, Hatamlou A. Multi-verse optimizer: a nature-inspired algorithm for global optimization. Neural Comput Appl. 2016;27:495\u2013513.","journal-title":"Neural Comput Appl"},{"key":"1260_CR38","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2024.128289","volume":"607","author":"A Qi","year":"2024","unstructured":"Qi A, Zhao D, Heidari AA, Liu L, Chen Y, Chen H. FATA: an efficient optimization method based on geophysics. Neurocomputing. 2024;607: 128289.","journal-title":"Neurocomputing"},{"key":"1260_CR39","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2023.122638","volume":"241","author":"J Lian","year":"2024","unstructured":"Lian J, Hui G. Human evolutionary optimization algorithm. Expert Syst Appl. 2024;241: 122638.","journal-title":"Expert Syst Appl"},{"issue":"3","key":"1260_CR40","doi-asserted-by":"publisher","first-page":"303","DOI":"10.1016\/j.cad.2010.12.015","volume":"43","author":"RV Rao","year":"2011","unstructured":"Rao RV, Savsani VJ, Vakharia D. Teaching\u2013learning-based optimization: a novel method for constrained mechanical design optimization problems. Comput Aided Des. 2011;43(3):303\u201315.","journal-title":"Comput Aided Des"},{"key":"1260_CR41","doi-asserted-by":"publisher","first-page":"28","DOI":"10.1016\/j.swevo.2013.12.005","volume":"16","author":"SC Satapathy","year":"2014","unstructured":"Satapathy SC, Naik A. Modified teaching\u2013learning-based optimization algorithm for global numerical optimization\u2014a comparative study. Swarm Evol Comput. 2014;16:28\u201337.","journal-title":"Swarm Evol Comput"},{"key":"1260_CR42","doi-asserted-by":"publisher","DOI":"10.1080\/00207721.2024.2367079","volume":"55","author":"J Lian","year":"2024","unstructured":"Lian J, et al. The educational competition optimizer. Int J Syst Sci. 2024;55: 1\u201338.","journal-title":"Int J Syst Sci"},{"key":"1260_CR43","doi-asserted-by":"publisher","DOI":"10.1016\/j.rineng.2024.102958","volume":"24","author":"S Ekinci","year":"2024","unstructured":"Ekinci S, Izci D, Can O, Bajaj M, Blazek V. Frequency regulation of PV-reheat thermal power system via a novel hybrid educational competition optimizer with pattern search and cascaded PDN-PI controller. Results Eng. 2024;24: 102958.","journal-title":"Results Eng"},{"key":"1260_CR44","doi-asserted-by":"publisher","first-page":"119231","DOI":"10.1016\/j.enconman.2024.119231","volume":"323","author":"B Saad","year":"2025","unstructured":"Saad B, El-Sehiemy RA, Hasanie HM, El-Dabah MA. Robust parameter estimation of proton exchange membrane fuel cell using Huber loss statistical function. Energy Convers Manage. 2025;323:119231.","journal-title":"Energy Convers Manage"},{"key":"1260_CR45","doi-asserted-by":"publisher","DOI":"10.1016\/j.est.2025.116381","volume":"120","author":"MM Emam","year":"2025","unstructured":"Emam MM, Abd El-Sattar H, Houssein EH, Kamel S. Optimized design and integration of an off-grid solar PV-biomass-battery hybrid energy system using an enhanced educational competition algorithm for cost-effective rural electrification. J Energy Storage. 2025;120: 116381.","journal-title":"J Energy Storage"},{"key":"1260_CR46","first-page":"57","volume":"2019","author":"SP Adam","year":"2019","unstructured":"Adam SP, Alexandropoulos S-AN, Pardalos PM, Vrahatis MN. No free lunch theorem: a review. Approximat Opt Algor Compl Appl. 2019;2019:57\u201382.","journal-title":"Approximat Opt Algor Compl Appl."},{"issue":"1","key":"1260_CR47","doi-asserted-by":"publisher","first-page":"67","DOI":"10.1109\/4235.585893","volume":"1","author":"DH Wolpert","year":"1997","unstructured":"Wolpert DH, Macready WG. No free lunch theorems for optimization. IEEE Trans Evol Comput. 1997;1(1):67\u201382.","journal-title":"IEEE Trans Evol Comput"},{"key":"1260_CR48","first-page":"1","volume":"2024","author":"OR Adegboye","year":"2024","unstructured":"Adegboye OR, Feda AK, Ojekemi OS, Agyekum EB, Elattar EE, Kamel S. Refinement of dynamic hunting leadership algorithm for enhanced numerical optimization. IEEE Access. 2024;2024:1.","journal-title":"IEEE Access"},{"issue":"2","key":"1260_CR49","doi-asserted-by":"publisher","first-page":"128","DOI":"10.1007\/s10586-024-04753-4","volume":"28","author":"OR Adegboye","year":"2025","unstructured":"Adegboye OR, Feda AK. Improved exponential distribution optimizer: enhancing global numerical optimization problem solving and optimizing machine learning paramseters. Cluster Comput. 2025;28(2):128.","journal-title":"Cluster Comput"},{"issue":"8","key":"1260_CR50","doi-asserted-by":"publisher","first-page":"4229","DOI":"10.1007\/s00521-023-09234-0","volume":"36","author":"SK Sahoo","year":"2024","unstructured":"Sahoo SK, Premkumar M, Saha AK, Houssein EH, Wanjari S, Emam MM. Multi-objective quasi-reflection learning and weight strategy-based moth flame optimization algorithm. Neural Comput Appl. 2024;36(8):4229\u201361.","journal-title":"Neural Comput Appl"},{"issue":"5","key":"1260_CR51","doi-asserted-by":"publisher","first-page":"6527","DOI":"10.1007\/s10586-024-04301-0","volume":"27","author":"SK Sahoo","year":"2024","unstructured":"Sahoo SK, Saha AK, Houssein EH, Premkumar M, Reang S, Emam MM. An arithmetic and geometric mean-based multi-objective moth-flame optimization algorithm. Cluster Comput. 2024;27(5):6527\u201361.","journal-title":"Cluster Comput"},{"key":"1260_CR52","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2024.112019","volume":"164","author":"M Jameel","year":"2024","unstructured":"Jameel M, Abouhawwash M. Revolutionizing optimization: An innovative nutcracker optimizer for single and multi-objective problems. Appl Soft Comput. 2024;164: 112019.","journal-title":"Appl Soft Comput"},{"key":"1260_CR53","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2023.121219","volume":"236","author":"F Zhu","year":"2024","unstructured":"Zhu F, Li G, Tang H, Li Y, Lv X, Wang X. Dung beetle optimization algorithm based on quantum computing and multi-strategy fusion for solving engineering problems. Expert Syst Appl. 2024;236: 121219.","journal-title":"Expert Syst Appl"},{"issue":"23","key":"1260_CR54","doi-asserted-by":"publisher","first-page":"17887","DOI":"10.1007\/s00500-023-09070-3","volume":"27","author":"J Li","year":"2023","unstructured":"Li J, Ren H, Chen H, Li C. Teaching\u2013learning guided salp swarm algorithm for global optimization tasks and feature selection. Soft Comput. 2023;27(23):17887\u2013908.","journal-title":"Soft Comput"},{"key":"1260_CR55","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2023.110664","volume":"146","author":"M Zhang","year":"2023","unstructured":"Zhang M, Chen H, Heidari AA, Cai Z, Aljehane NO, Mansour RF. Ocrun: an oppositional Runge Kutta optimizer with cuckoo search for global optimization and feature selection. Appl Soft Comput. 2023;146: 110664.","journal-title":"Appl Soft Comput"},{"key":"1260_CR56","volume":"11","author":"H Yu","year":"2024","unstructured":"Yu H, Zhao Z, Cai Q, Heidari AA, Xu X, Chen H. Slime mould algorithm with horizontal crossover and adaptive evolutionary strategy: performance design for engineering problems. J Comput Des Eng. 2024;11: qwae057.","journal-title":"J Comput Des Eng"},{"key":"1260_CR57","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2023.110701","volume":"146","author":"Q Yang","year":"2023","unstructured":"Yang Q, Liu J, Wu Z, He S. A fusion algorithm based on whale and grey wolf optimization algorithm for solving real-world optimization problems. Appl Soft Comput. 2023;146: 110701.","journal-title":"Appl Soft Comput"},{"key":"1260_CR58","doi-asserted-by":"publisher","first-page":"197","DOI":"10.1016\/j.asoc.2018.02.049","volume":"67","author":"X Zhang","year":"2018","unstructured":"Zhang X, Kang Q, Cheng J, Wang X. A novel hybrid algorithm based on biogeography-based optimization and grey wolf optimizer. Appl Soft Comput. 2018;67:197\u2013214.","journal-title":"Appl Soft Comput"},{"key":"1260_CR59","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2022.119327","volume":"215","author":"X Yu","year":"2023","unstructured":"Yu X, Jiang N, Wang X, Li M. A hybrid algorithm based on grey wolf optimizer and differential evolution for UAV path planning. Expert Syst Appl. 2023;215: 119327.","journal-title":"Expert Syst Appl"},{"issue":"10","key":"1260_CR60","doi-asserted-by":"publisher","first-page":"4863","DOI":"10.1007\/s00500-022-06873-8","volume":"26","author":"S Mahajan","year":"2022","unstructured":"Mahajan S, Abualigah L, Pandit AK, Altalhi M. Hybrid Aquila optimizer with arithmetic optimization algorithm for global optimization tasks. Soft Comput. 2022;26(10):4863\u201381.","journal-title":"Soft Comput"},{"issue":"4","key":"1260_CR61","doi-asserted-by":"publisher","first-page":"2811","DOI":"10.1007\/s10462-022-10218-0","volume":"56","author":"SK Sahoo","year":"2023","unstructured":"Sahoo SK, Saha AK, Nama S, Masdari M. An improved moth flame optimization algorithm based on modified dynamic opposite learning strategy. Artif Intell Rev. 2023;56(4):2811\u201369.","journal-title":"Artif Intell Rev"},{"key":"1260_CR62","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2025.112995","volume":"174","author":"R Zhong","year":"2025","unstructured":"Zhong R, Wang Z, Zhang Y, Lian JJ, Yu J, Chen H. Integrating competitive framework into differential evolution: comprehensive performance analysis and application in brain tumor detection. Appl Soft Comput. 2025;174: 112995.","journal-title":"Appl Soft Comput"},{"issue":"12","key":"1260_CR63","doi-asserted-by":"publisher","first-page":"1238","DOI":"10.1038\/s42256-022-00579-0","volume":"4","author":"J Kudela","year":"2022","unstructured":"Kudela J. A critical problem in benchmarking and analysis of evolutionary computation methods. Nat Mach Intell. 2022;4(12):1238\u201345.","journal-title":"Nat Mach Intell"},{"issue":"1","key":"1260_CR64","first-page":"6505253","volume":"2021","author":"C Ouyang","year":"2021","unstructured":"Ouyang C, Qiu Y, Zhu D. Adaptive spiral flying sparrow search algorithm. Sci Program. 2021;2021(1):6505253.","journal-title":"Sci Program"},{"issue":"1","key":"1260_CR65","doi-asserted-by":"publisher","first-page":"68","DOI":"10.1007\/s40430-022-04008-6","volume":"45","author":"S Ekinci","year":"2023","unstructured":"Ekinci S, Izci D, Abualigah L. A novel balanced Aquila optimizer using random learning and Nelder-mead simplex search mechanisms for air\u2013fuel ratio system control. J Braz Soc Mech Sci Eng. 2023;45(1):68.","journal-title":"J Braz Soc Mech Sci Eng"},{"issue":"1","key":"1260_CR66","doi-asserted-by":"publisher","first-page":"45","DOI":"10.1080\/00401706.1975.10489269","volume":"17","author":"DM Olsson","year":"1975","unstructured":"Olsson DM, Nelson LS. The nelder-mead simplex procedure for function minimization. Technometrics. 1975;17(1):45\u201351.","journal-title":"Technometrics"},{"issue":"7","key":"1260_CR67","doi-asserted-by":"publisher","first-page":"7305","DOI":"10.1007\/s11227-022-04959-6","volume":"79","author":"J Xue","year":"2023","unstructured":"Xue J, Shen B. Dung beetle optimizer: a new meta-heuristic algorithm for global optimization. J Supercomput. 2023;79(7):7305\u201336.","journal-title":"J Supercomput"},{"key":"1260_CR68","doi-asserted-by":"publisher","DOI":"10.1016\/j.cma.2020.113609","volume":"376","author":"L Abualigah","year":"2021","unstructured":"Abualigah L, Diabat A, Mirjalili S, Elaziz MA, Gandomi AH. The arithmetic optimization algorithm. Comput Methods Appl Mech Eng. 2021;376: 113609.","journal-title":"Comput Methods Appl Mech Eng"},{"key":"1260_CR69","doi-asserted-by":"publisher","first-page":"51","DOI":"10.1016\/j.advengsoft.2016.01.008","volume":"95","author":"S Mirjalili","year":"2016","unstructured":"Mirjalili S, Lewis A. The whale optimization algorithm. Adv Eng Softw. 2016;95:51\u201367.","journal-title":"Adv Eng Softw"},{"key":"1260_CR70","doi-asserted-by":"publisher","first-page":"120","DOI":"10.1016\/j.knosys.2015.12.022","volume":"96","author":"S Mirjalili","year":"2016","unstructured":"Mirjalili S. SCA: a sine cosine algorithm for solving optimization problems. Knowl-Based Syst. 2016;96:120\u201333.","journal-title":"Knowl-Based Syst"},{"key":"1260_CR71","doi-asserted-by":"crossref","unstructured":"Kumar A, Das S, Zelinka I. A modified covariance matrix adaptation evolution strategy for real-world constrained optimization problems. In: Proceedings of the 2020 genetic and evolutionary computation conference companion, 2020. pp. 11\u201312.","DOI":"10.1145\/3377929.3398185"},{"key":"1260_CR72","doi-asserted-by":"crossref","unstructured":"Fan Z, Fang Y, Li W, Yuan Y, Wang Z, Bian X. LSHADE44 with an improved $\\epsilon $ constraint-handling method for solving constrained single-objective optimization problems. In: 2018 IEEE congress on evolutionary computation (CEC). IEEE. 2018. pp. 1\u20138.","DOI":"10.1109\/CEC.2018.8477943"},{"key":"1260_CR73","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2019.113033","volume":"162","author":"KM Sallam","year":"2020","unstructured":"Sallam KM, Elsayed SM, Sarker RA, Essam DL. Landscape-assisted multi-operator differential evolution for solving constrained optimization problems. Expert Syst Appl. 2020;162: 113033.","journal-title":"Expert Syst Appl"},{"key":"1260_CR74","doi-asserted-by":"crossref","unstructured":"Gurrola-Ramos J, Hern\u00e0ndez-Aguirre A, Dalmau-Cede\u00f1o O. COLSHADE for real-world single-objective constrained optimization problems. In: 2020 IEEE congress on evolutionary computation (CEC), IEEE. 2020. pp. 1\u20138.","DOI":"10.1109\/CEC48606.2020.9185583"},{"issue":"1","key":"1260_CR75","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1111\/itor.12001","volume":"22","author":"K S\u00f6rensen","year":"2015","unstructured":"S\u00f6rensen K. Metaheuristics\u2014the metaphor exposed. Int Trans Oper Res. 2015;22(1):3\u201318.","journal-title":"Int Trans Oper Res"},{"issue":"6","key":"1260_CR76","doi-asserted-by":"publisher","first-page":"2945","DOI":"10.1111\/itor.13176","volume":"30","author":"CL Camacho-Villal\u00f3n","year":"2023","unstructured":"Camacho-Villal\u00f3n CL, Dorigo M, St\u00fctzle T. Exposing the grey wolf, moth-flame, whale, firefly, bat, and antlion algorithms: six misleading optimization techniques inspired by bestial metaphors. Int Trans Oper Res. 2023;30(6):2945\u201371.","journal-title":"Int Trans Oper Res"},{"key":"1260_CR77","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2023.121544","volume":"237","author":"L Deng","year":"2024","unstructured":"Deng L, Liu S. Deficiencies of the whale optimization algorithm and its validation method. Expert Syst Appl. 2024;237: 121544.","journal-title":"Expert Syst Appl"},{"key":"1260_CR78","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2024.111696","volume":"160","author":"L Deng","year":"2024","unstructured":"Deng L, Liu S. Metaheuristics exposed: unmasking the design pitfalls of arithmetic optimization algorithm in benchmarking. Appl Soft Comput. 2024;160: 111696.","journal-title":"Appl Soft Comput"},{"key":"1260_CR79","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2024.111574","volume":"158","author":"L Deng","year":"2024","unstructured":"Deng L, Liu S. Exposing the chimp optimization algorithm: a misleading metaheuristic technique with structural bias. Appl Soft Comput. 2024;158: 111574.","journal-title":"Appl Soft Comput"},{"key":"1260_CR80","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2023.122638","volume":"241","author":"J Lian","year":"2023","unstructured":"Lian J, Hui G. Human evolutionary optimization algorithm. Expert Syst Appl. 2023;241: 122638.","journal-title":"Expert Syst Appl"},{"key":"1260_CR81","doi-asserted-by":"publisher","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. Grey wolf optimizer. Adv Eng Softw. 2014;69:46\u201361.","journal-title":"Adv Eng Softw"},{"key":"1260_CR82","doi-asserted-by":"publisher","first-page":"30","DOI":"10.1016\/j.advengsoft.2017.01.004","volume":"105","author":"S Saremi","year":"2017","unstructured":"Saremi S, Mirjalili S, Lewis A. Grasshopper optimisation algorithm: theory and application. Adv Eng Softw. 2017;105:30\u201347.","journal-title":"Adv Eng Softw"},{"issue":"2","key":"1260_CR83","doi-asserted-by":"publisher","first-page":"82","DOI":"10.1109\/4235.771163","volume":"3","author":"X Yao","year":"1999","unstructured":"Yao X, Liu Y, Lin G. Evolutionary programming made faster. IEEE Trans Evol Comput. 1999;3(2):82\u2013102.","journal-title":"IEEE Trans Evol Comput"},{"issue":"2","key":"1260_CR84","first-page":"2013","volume":"635","author":"JJ Liang","year":"2013","unstructured":"Liang JJ, Qu BY, Suganthan PN. Problem definitions and evaluation criteria for the CEC 2014 special session and competition on single objective real-parameter numerical optimization. Comput Intell Lab Zhengzhou Univ Zhengzhou China Tech Rep Nanyang Technol Univ Singapore. 2013;635(2):2013.","journal-title":"Comput Intell Lab Zhengzhou Univ Zhengzhou China Tech Rep Nanyang Technol Univ Singapore"},{"key":"1260_CR85","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2021.104910","volume":"138","author":"L Liu","year":"2021","unstructured":"Liu L, et al. Performance optimization of differential evolution with slime mould algorithm for multilevel breast cancer image segmentation. Comput Biol Med. 2021;138: 104910.","journal-title":"Comput Biol Med"},{"key":"1260_CR86","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2021.105206","volume":"143","author":"J Xia","year":"2022","unstructured":"Xia J, et al. Performance optimization of support vector machine with oppositional grasshopper optimization for acute appendicitis diagnosis. Comput Biol Med. 2022;143: 105206.","journal-title":"Comput Biol Med"},{"key":"1260_CR87","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2021.104427","volume":"134","author":"S Zhao","year":"2021","unstructured":"Zhao S, et al. Multilevel threshold image segmentation with diffusion association slime mould algorithm and Renyi\u2019s entropy for chronic obstructive pulmonary disease. Comput Biol Med. 2021;134: 104427.","journal-title":"Comput Biol Med"},{"key":"1260_CR88","doi-asserted-by":"crossref","unstructured":"Lian J, Wu P, Han W, Xie Y, Zheng Y, Xu Y, ... Hui G. Discrimination of Chinese prickly ash origin place using electronic nose system and feature extraction with support vector boosting machine. Cogent Food Agric. 2025;11(1):2464939.","DOI":"10.1080\/23311932.2025.2464939"},{"key":"1260_CR89","doi-asserted-by":"crossref","unstructured":"Lian JJ, Ouyang K, Zhong R, Zhang Y, Luo S, Ma L, ... Chen H. Trend-Aware Mechanism for metaheuristic algorithms. Appl Soft Comput.\n2025;113505.","DOI":"10.1016\/j.asoc.2025.113505"},{"key":"1260_CR90","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2023.106549","volume":"124","author":"V Garg","year":"2023","unstructured":"Garg V, Deep K, Bansal S. Improved teaching learning algorithm with Laplacian operator for solving nonlinear engineering optimization problems. Eng Appl Artif Intell. 2023;124: 106549.","journal-title":"Eng Appl Artif Intell"},{"key":"1260_CR91","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2023.106207","volume":"123","author":"B Shen","year":"2023","unstructured":"Shen B, Khishe M, Mirjalili S. Evolving marine predators algorithm by dynamic foraging strategy for real-world engineering optimization problems. Eng Appl Artif Intell. 2023;123: 106207.","journal-title":"Eng Appl Artif Intell"},{"key":"1260_CR92","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2023.107532","volume":"128","author":"R Sowmya","year":"2024","unstructured":"Sowmya R, Premkumar M, Jangir P. Newton-raphson-based optimizer: a new population-based metaheuristic algorithm for continuous optimization problems. Eng Appl Artif Intell. 2024;128: 107532.","journal-title":"Eng Appl Artif Intell"},{"key":"1260_CR93","doi-asserted-by":"publisher","DOI":"10.1016\/j.swevo.2020.100693","volume":"56","author":"A Kumar","year":"2020","unstructured":"Kumar A, Wu G, Ali MZ, Mallipeddi R, Suganthan PN, Das S. A test-suite of non-convex constrained optimization problems from the real-world and some baseline results. Swarm Evol Comput. 2020;56: 100693.","journal-title":"Swarm Evol Comput"},{"issue":"2","key":"1260_CR94","doi-asserted-by":"publisher","first-page":"551","DOI":"10.2514\/1.37030","volume":"32","author":"TR Jorris","year":"2009","unstructured":"Jorris TR, Cobb RG. Three-dimensional trajectory optimization satisfying waypoint and no-fly zone constraints. J Guid Control Dyn. 2009;32(2):551\u201372.","journal-title":"J Guid Control Dyn"},{"issue":"6","key":"1260_CR95","doi-asserted-by":"publisher","first-page":"1407","DOI":"10.1080\/00207721.2014.929191","volume":"47","author":"Y-B Chen","year":"2016","unstructured":"Chen Y-B, Luo G-C, Mei Y-S, Yu J-Q, Su X-L. Uav path planning using artificial potential field method updated by optimal control theory. Int J Syst Sci. 2016;47(6):1407\u201320.","journal-title":"Int J Syst Sci"},{"issue":"1","key":"1260_CR96","doi-asserted-by":"publisher","first-page":"132","DOI":"10.1109\/TII.2012.2198665","volume":"9","author":"V Roberge","year":"2012","unstructured":"Roberge V, Tarbouchi M, Labont\u00e9 G. Comparison of parallel genetic algorithm and particle swarm optimization for real-time UAV path planning. IEEE Trans Ind Inform. 2012;9(1):132\u201341.","journal-title":"IEEE Trans Ind Inform"}],"container-title":["Journal of Big Data"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s40537-025-01260-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s40537-025-01260-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s40537-025-01260-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,10]],"date-time":"2025-09-10T03:57:58Z","timestamp":1757476678000},"score":1,"resource":{"primary":{"URL":"https:\/\/journalofbigdata.springeropen.com\/articles\/10.1186\/s40537-025-01260-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8,19]]},"references-count":96,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2025,12]]}},"alternative-id":["1260"],"URL":"https:\/\/doi.org\/10.1186\/s40537-025-01260-0","relation":{},"ISSN":["2196-1115"],"issn-type":[{"value":"2196-1115","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,8,19]]},"assertion":[{"value":"18 January 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"3 August 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 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":"Not applicable.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"The authors declare no competing interests.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"200"}}