{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,16]],"date-time":"2026-06-16T14:41:12Z","timestamp":1781620872104,"version":"3.54.5"},"reference-count":189,"publisher":"Springer Science and Business Media LLC","issue":"6","license":[{"start":{"date-parts":[[2024,5,9]],"date-time":"2024-05-09T00:00:00Z","timestamp":1715212800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2024,5,9]],"date-time":"2024-05-09T00:00:00Z","timestamp":1715212800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/100014717","name":"National Outstanding Youth Science Fund Project of National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62341210"],"award-info":[{"award-number":["62341210"]}],"id":[{"id":"10.13039\/100014717","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Science and Technology Development Plan for Baise City","award":["20233654"],"award-info":[{"award-number":["20233654"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Artif Intell Rev"],"abstract":"<jats:title>Abstract<\/jats:title><jats:p>In this study, the Learning Search Algorithm (LSA) is introduced as an innovative optimization algorithm that draws inspiration from swarm intelligence principles and mimics the social learning behavior observed in humans. The LSA algorithm optimizes the search process by integrating historical experience and real-time social information, enabling it to effectively navigate complex problem spaces. By doing so, it enhances its global development capability and provides efficient solutions to challenging optimization tasks. Additionally, the algorithm improves the collective learning capacity by incorporating teaching and active learning behaviors within the population, leading to improved local development capabilities. Furthermore, a dynamic adaptive control factor is utilized to regulate the algorithm\u2019s global exploration and local development abilities. The proposed algorithm is rigorously evaluated using 40 benchmark test functions from IEEE CEC 2014 and CEC 2020, and compared against nine established evolutionary algorithms as well as 11 recently improved algorithms. The experimental results demonstrate the superiority of the LSA algorithm, as it achieves the top rank in the Friedman rank-sum test, highlighting its power and competitiveness. Moreover, the LSA algorithm is successfully applied to solve six real-world engineering problems and 15 UCI datasets of feature selection problems, showcasing its significant advantages and potential for practical applications in engineering problems and feature selection problems.<\/jats:p>","DOI":"10.1007\/s10462-024-10767-6","type":"journal-article","created":{"date-parts":[[2024,5,9]],"date-time":"2024-05-09T23:02:21Z","timestamp":1715295741000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Learning search algorithm: framework and comprehensive performance for solving optimization problems"],"prefix":"10.1007","volume":"57","author":[{"given":"Chiwen","family":"Qu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaoning","family":"Peng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qilan","family":"Zeng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,5,9]]},"reference":[{"issue":"21","key":"10767_CR1","doi-asserted-by":"crossref","first-page":"14079","DOI":"10.1007\/s00521-021-05960-5","volume":"33","author":"M Abd Elaziz","year":"2021","unstructured":"Abd Elaziz M, Dahou A, Abualigah L, Yu L, Alshinwan M, Khasawneh AM, Lu S (2021) Advanced metaheuristic optimization techniques in applications of deep neural networks: a review. Neural Comput Appl 33(21):14079\u201314099","journal-title":"Neural Comput Appl"},{"key":"10767_CR2","doi-asserted-by":"crossref","unstructured":"Abdel-Basset M, El-Shahat D, Jameel M et al (2023) Exponential distribution optimizer (EDO): a novel math-inspired algorithm for global optimization and engineering problems. Artif Intell Rev:1\u201372","DOI":"10.1007\/s10462-023-10403-9"},{"key":"10767_CR3","doi-asserted-by":"crossref","unstructured":"Abdesslem layeb (2023) TSALSHADE: improved LSHADE algorithm with tangent search. MATLAB central file exchange. https:\/\/www.mathworks.com\/maTLABCentral\/fileexchange\/123400-tsalshade-improved-lshade-algorithm-with-tangent-search","DOI":"10.1504\/IJCSE.2024.10062887"},{"issue":"21","key":"10767_CR4","doi-asserted-by":"crossref","first-page":"2689","DOI":"10.3390\/electronics10212689","volume":"10","author":"MGM Abdolrasol","year":"2021","unstructured":"Abdolrasol MGM, Hussain SMS, Ustun TS, Sarker MR, Hannan MA, Mohamed R, Ali JA, Mekhilef S, Milad A (2021) Artificial Neural networks based optimization techniques: a review. Electronics 10(21):2689","journal-title":"Electronics"},{"issue":"15","key":"10767_CR5","doi-asserted-by":"crossref","first-page":"10167","DOI":"10.1007\/s00500-021-05939-3","volume":"25","author":"BH Abed-Alguni","year":"2021","unstructured":"Abed-Alguni BH, Alawad NA, Barhoush M et al (2021) Exploratory cuckoo search for solving single-objective optimization problems[J]. Soft Comput 25(15):10167\u201310180","journal-title":"Soft Comput"},{"issue":"15","key":"10767_CR6","doi-asserted-by":"crossref","first-page":"11195","DOI":"10.1007\/s00521-019-04629-4","volume":"32","author":"L Abualigah","year":"2020","unstructured":"Abualigah L, Shehab M, Alshinwan M et al (2020) Salp swarm algorithm: a comprehensive survey. Neural Comput Appl 32(15):11195\u201311215","journal-title":"Neural Comput Appl"},{"key":"10767_CR7","doi-asserted-by":"crossref","first-page":"113609","DOI":"10.1016\/j.cma.2020.113609","volume":"376","author":"L Abualigah","year":"2021","unstructured":"Abualigah L, Diabat A, Mirjalili S et al (2021) The arithmetic optimization algorithm. Comput Methods Appl Mech Eng 376:113609","journal-title":"Comput Methods Appl Mech Eng"},{"key":"10767_CR8","doi-asserted-by":"crossref","DOI":"10.1016\/j.cma.2022.114570","volume":"391","author":"JO Agushaka","year":"2022","unstructured":"Agushaka JO, Ezugwu AE, Abualigah L (2022) Dwarf mongoose optimization algorithm. Comput Methods Appl Mech Eng 391:114570","journal-title":"Comput Methods Appl Mech Eng"},{"key":"10767_CR9","doi-asserted-by":"crossref","first-page":"116516","DOI":"10.1016\/j.eswa.2022.116516","volume":"195","author":"I Ahmadianfar","year":"2022","unstructured":"Ahmadianfar I, Heidari AA, Noshadian S et al (2022) INFO: an efficient optimization algorithm based on weighted mean of vectors. Expert Syst Appl 195:116516","journal-title":"Expert Syst Appl"},{"issue":"1","key":"10767_CR10","doi-asserted-by":"crossref","first-page":"362","DOI":"10.3906\/elk-1804-56","volume":"27","author":"I Ahmia","year":"2019","unstructured":"Ahmia I, Aider M (2019) A novel metaheuristic optimization algorithm: the monarchy metaheuristic. Turk J Electr Eng Comput Sci 27(1):362\u2013376","journal-title":"Turk J Electr Eng Comput Sci"},{"issue":"13","key":"10767_CR11","doi-asserted-by":"crossref","first-page":"499","DOI":"10.1049\/ell2.12176","volume":"57","author":"E Akbari","year":"2021","unstructured":"Akbari E, Rahimnejad A, Gadsden SA (2021) A greedy non-hierarchical grey wolf optimizer for real-world optimization. Electron Lett 57(13):499\u2013501","journal-title":"Electron Lett"},{"issue":"2","key":"10767_CR12","doi-asserted-by":"crossref","first-page":"846","DOI":"10.3390\/en16020846","volume":"16","author":"MH Ali","year":"2023","unstructured":"Ali MH, El-Rifaie AM, Youssef AAF et al (2023) Techno-economic strategy for the load dispatch and power flow in power grids using peafowl optimization algorithm. Energies 16(2):846","journal-title":"Energies"},{"issue":"3","key":"10767_CR13","doi-asserted-by":"crossref","first-page":"2237","DOI":"10.1007\/s10462-019-09732-5","volume":"53","author":"HA Alsattar","year":"2020","unstructured":"Alsattar HA, Zaidan AA, Zaidan BB (2020) Novel meta-heuristic bald eagle search optimisation algorithm. Artif Intell Rev 53(3):2237\u20132264","journal-title":"Artif Intell Rev"},{"issue":"3","key":"10767_CR14","doi-asserted-by":"crossref","first-page":"351","DOI":"10.1002\/nme.2904","volume":"84","author":"VS Arag\u00f3n","year":"2010","unstructured":"Arag\u00f3n VS, Esquivel SC, Coello CAC (2010) A modified version of a T-cell algorithm for constrained optimization problems. Internat J Numer Methods Engrg 84(3):351\u2013378","journal-title":"Internat J Numer Methods Engrg"},{"key":"10767_CR15","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 23:715\u2013734","journal-title":"Soft Comput"},{"key":"10767_CR16","doi-asserted-by":"crossref","first-page":"113702","DOI":"10.1016\/j.eswa.2020.113702","volume":"161","author":"Q Askari","year":"2020","unstructured":"Askari Q, Saeed M, Younas I (2020) Heap-based optimizer inspired by corporate rank hierarchy for global optimization. Expert Syst Appl 161:113702","journal-title":"Expert Syst Appl"},{"key":"10767_CR17","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.compstruc.2016.03.001","volume":"169","author":"A Askarzadeh","year":"2016","unstructured":"Askarzadeh A (2016) A novel metaheuristic method for solving constrained engineering optimization problems: crow search algorithm. Comput Struct 169:1\u201312","journal-title":"Comput Struct"},{"key":"10767_CR18","doi-asserted-by":"crossref","first-page":"232","DOI":"10.1016\/j.asoc.2018.02.025","volume":"66","author":"IB Aydilek","year":"2018","unstructured":"Aydilek IB (2018) A hybrid firefly and particle swarm optimization algorithm for computationally expensive numerical problems. Appl Soft Comput 66:232\u2013249","journal-title":"Appl Soft Comput"},{"key":"10767_CR19","doi-asserted-by":"crossref","first-page":"25073","DOI":"10.1109\/ACCESS.2022.3153493","volume":"10","author":"TSLV Ayyarao","year":"2022","unstructured":"Ayyarao TSLV, Ramakrishna NSS, Elavarasan RM et al (2022) War strategy optimization algorithm: a new effective metaheuristic algorithm for global optimization. IEEE Access 10:25073\u201325105","journal-title":"IEEE Access"},{"key":"10767_CR20","doi-asserted-by":"crossref","unstructured":"Bennett S (2011) Learning behaviors and learning spaces. portal: libraries and the academy. 11(3):765\u2013789","DOI":"10.1353\/pla.2011.0033"},{"key":"10767_CR21","doi-asserted-by":"crossref","unstructured":"Bernardino HS, Barbosa HJC, Lemonge ACC, Fonseca LG (2008) A new hybrid AIS-GA for constrained optimization problems in mechanical engineering. In: 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence). pp 1455\u20131462","DOI":"10.1109\/CEC.2008.4630985"},{"issue":"1","key":"10767_CR22","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1214\/ss\/1177011077","volume":"8","author":"D Bertsimas","year":"1993","unstructured":"Bertsimas D, Tsitsiklis J (1993) Simulated annealing. Stat Sci 8(1):10\u201315","journal-title":"Stat Sci"},{"key":"10767_CR23","doi-asserted-by":"crossref","first-page":"114685","DOI":"10.1016\/j.eswa.2021.114685","volume":"174","author":"MS Braik","year":"2021","unstructured":"Braik MS (2021) Chameleon swarm algorithm: a bio-inspired optimizer for solving engineering design problems. Expert Syst Appl 174:114685","journal-title":"Expert Syst Appl"},{"issue":"7","key":"10767_CR24","doi-asserted-by":"crossref","first-page":"2515","DOI":"10.1007\/s00521-020-05145-6","volume":"33","author":"M Braik","year":"2021","unstructured":"Braik M, Sheta A, Al-Hiary H (2021) A novel meta-heuristic search algorithm for solving optimization problems: capuchin search algorithm. Neural Comput Appl 33(7):2515\u20132547","journal-title":"Neural Comput Appl"},{"issue":"7","key":"10767_CR25","doi-asserted-by":"crossref","first-page":"1587","DOI":"10.1007\/s00521-015-1826-y","volume":"26","author":"I Brajevic","year":"2015","unstructured":"Brajevic I (2015) Crossover-based artificial bee colony algorithm for constrained optimization problems. Neural Comput Appl 26(7):1587\u20131601","journal-title":"Neural Comput Appl"},{"key":"10767_CR26","doi-asserted-by":"crossref","first-page":"bxy133","DOI":"10.1093\/comjnl\/bxy133","volume":"2019","author":"G Brammya","year":"2019","unstructured":"Brammya G, Praveena S, Ninu Preetha NS et al (2019) Deer hunting optimization algorithm: a new nature-inspired meta-heuristic paradigm. Comput J 2019:bxy133","journal-title":"Comput J"},{"issue":"1","key":"10767_CR27","first-page":"18","volume":"53","author":"JS Bruner","year":"1971","unstructured":"Bruner JS (1971) \u201cThe process of education\u201d revisited. Phi Delta Kappan 53(1):18\u201321","journal-title":"Phi Delta Kappan"},{"key":"10767_CR28","doi-asserted-by":"crossref","unstructured":"Bruner JS (2009) The process of education. Harvard University Press","DOI":"10.2307\/j.ctvk12qst"},{"key":"10767_CR29","doi-asserted-by":"crossref","first-page":"4797","DOI":"10.1007\/s00500-022-06865-8","volume":"26","author":"H Carreon-Ortiz","year":"2022","unstructured":"Carreon-Ortiz H, Valdez F (2022) A new mycorrhized tree optimization nature-inspired algorithm. Soft Comput 26:4797\u20134817","journal-title":"Soft Comput"},{"issue":"5","key":"10767_CR30","doi-asserted-by":"crossref","first-page":"4998","DOI":"10.1016\/j.eswa.2010.09.151","volume":"38","author":"A Chander","year":"2011","unstructured":"Chander A, Chatterjee A, Siarry P (2011) A new social and momentum component adaptive PSO algorithm for image segmentation. Expert Syst Appl 38(5):4998\u20135004","journal-title":"Expert Syst Appl"},{"key":"10767_CR31","doi-asserted-by":"crossref","first-page":"65944","DOI":"10.1109\/ACCESS.2019.2916718","volume":"7","author":"J Chen","year":"2019","unstructured":"Chen J, Xu H, Wu J et al (2019) Deer crossing road detection with roadside LiDAR sensor. IEEE Access 7:65944\u201365954","journal-title":"IEEE Access"},{"key":"10767_CR32","volume":"144","author":"H Chen","year":"2020","unstructured":"Chen H, Heidari AA, Zhao X et al (2020a) Advanced orthogonal learning-driven multi-swarm sine cosine optimization: framework and case studies. Expert Syst Appl 144:113113","journal-title":"Expert Syst Appl"},{"key":"10767_CR33","doi-asserted-by":"crossref","first-page":"118778","DOI":"10.1016\/j.jclepro.2019.118778","volume":"244","author":"H Chen","year":"2020","unstructured":"Chen H, Jiao S, Wang M, Heidari AA, Zhao X (2020b) Parameters identification of photovoltaic cells and modules using diversification-enriched Harris hawks optimization with chaotic drifts. J Clean Prod 244:118778","journal-title":"J Clean Prod"},{"key":"10767_CR34","doi-asserted-by":"crossref","first-page":"104805","DOI":"10.1016\/j.engappai.2022.104805","volume":"111","author":"P Chen","year":"2022","unstructured":"Chen P, Zhou S, Zhang Q et al (2022) A meta-inspired termite queen algorithm for global optimization and engineering design problems. Eng Appl Artif Intell 111:104805","journal-title":"Eng Appl Artif Intell"},{"issue":"2","key":"10767_CR35","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1515\/jaiscr-2015-0001","volume":"4","author":"S Cheng","year":"2014","unstructured":"Cheng S, Shi Y, Qin Q et al (2014) Population diversity maintenance in brain storm optimization algorithm[J]. J Artif Intell Soft Comput Res 4(2):83\u201397","journal-title":"J Artif Intell Soft Comput Res"},{"issue":"5","key":"10767_CR36","doi-asserted-by":"crossref","first-page":"829","DOI":"10.1002\/(SICI)1097-0207(19960315)39:5<829::AID-NME884>3.0.CO;2-U","volume":"39","author":"H Chickermane","year":"1996","unstructured":"Chickermane H, Gea HC (1996) Structural optimization using a new local approximation method. Internat J Numer Methods Engrg 39(5):829\u2013846","journal-title":"Internat J Numer Methods Engrg"},{"key":"10767_CR37","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2022.116924","volume":"198","author":"N Chopra","year":"2022","unstructured":"Chopra N, Ansari MM (2022) Golden jackal optimization: a novel nature-inspired optimizer for engineering applications. Expert Syst Appl 198:116924","journal-title":"Expert Syst Appl"},{"key":"10767_CR38","doi-asserted-by":"crossref","first-page":"130750","DOI":"10.1155\/2013\/130750","volume":"5","author":"S Chun","year":"2013","unstructured":"Chun S, Kim YT, Kim TH (2013) A diversity-enhanced constrained particle swarm optimizer for mixed integer-discrete-continuous engineering design problems. Adv Mech Eng 5:130750","journal-title":"Adv Mech Eng"},{"issue":"5","key":"10767_CR39","doi-asserted-by":"crossref","first-page":"607","DOI":"10.1080\/03052150410001704845","volume":"36","author":"CAC Coello","year":"2004","unstructured":"Coello CAC, Cort\u00e9s NC (2004) Hybridizing a genetic algorithm with an artificial immune system for global optimization. Eng Optim 36(5):607\u2013634","journal-title":"Eng Optim"},{"issue":"1","key":"10767_CR40","doi-asserted-by":"crossref","first-page":"4","DOI":"10.1109\/TEVC.2010.2059031","volume":"15","author":"S Das","year":"2010","unstructured":"Das S, Suganthan PN (2010) Differential evolution: a survey of the state-of-the-art. IEEE Trans Evol Comput 15(1):4\u201331","journal-title":"IEEE Trans Evol Comput"},{"key":"10767_CR41","doi-asserted-by":"crossref","first-page":"1126450","DOI":"10.3389\/fmech.2022.1126450","volume":"8","author":"M Dehghani","year":"2023","unstructured":"Dehghani M, Trojovsk\u00fd P (2023) Osprey optimization algorithm: a new bio-inspired metaheuristic algorithm for solving engineering optimization problems. Front Mech Eng 8:1126450","journal-title":"Front Mech Eng"},{"key":"10767_CR42","doi-asserted-by":"crossref","first-page":"162059","DOI":"10.1109\/ACCESS.2021.3133286","volume":"9","author":"M Dehghani","year":"2021","unstructured":"Dehghani M, Hub\u00e1lovsk\u00fd \u0160, Trojovsk\u00fd P (2021) Northern goshawk optimization: a new swarm-based algorithm for solving optimization problems. Ieee Access 9:162059\u2013162080","journal-title":"Ieee Access"},{"key":"10767_CR43","doi-asserted-by":"crossref","first-page":"19599","DOI":"10.1109\/ACCESS.2022.3151641","volume":"10","author":"M Dehghani","year":"2022","unstructured":"Dehghani M, Hub\u00e1lovsk\u00fd \u0160, Trojovsk\u00fd P (2022a) Tasmanian devil optimization: a new bio-inspired optimization algorithm for solving optimization algorithm. IEEE Access 10:19599\u201319620","journal-title":"IEEE Access"},{"key":"10767_CR44","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2022.110011","volume":"259","author":"M Dehghani","year":"2023","unstructured":"Dehghani M, Montazeri Z, Trojovsk\u00e1 E et al (2023) Coati optimization algorithm: a new bio-inspired metaheuristic algorithm for solving optimization problems. Knowl-Based Syst 259:110011","journal-title":"Knowl-Based Syst"},{"key":"10767_CR45","doi-asserted-by":"publisher","unstructured":"Dehghani M, Trojovsk\u00e1 E, Trojovsk\u00fd P (2022b) Driving training-based optimization: a new human-based metaheuristic algorithm for solving optimization problems. 4. https:\/\/doi.org\/10.21203\/rs.3.rs-1506972\/v1","DOI":"10.21203\/rs.3.rs-1506972\/v1"},{"key":"10767_CR46","doi-asserted-by":"crossref","first-page":"107574","DOI":"10.1016\/j.asoc.2021.107574","volume":"109","author":"A Dehkordi","year":"2021","unstructured":"Dehkordi A, Sadiq A, Mirjalili S et al (2021) Nonlinear-based chaotic harris hawks optimizer: algorithm and internet of vehicles application. Appl Soft Comput 109:107574","journal-title":"Appl Soft Comput"},{"issue":"5","key":"10767_CR47","doi-asserted-by":"crossref","first-page":"1194","DOI":"10.1007\/s12083-019-00765-9","volume":"12","author":"D Dhanya","year":"2019","unstructured":"Dhanya D, Arivudainambi D (2019) Dolphin partner optimization based secure and qualified virtual machine for resource allocation with streamline security analysis. Peer- Peer Netw Appl 12(5):1194\u20131213","journal-title":"Peer- Peer Netw Appl"},{"key":"10767_CR48","doi-asserted-by":"crossref","first-page":"148","DOI":"10.1016\/j.engappai.2019.03.021","volume":"82","author":"G Dhiman","year":"2019","unstructured":"Dhiman G, Kaur A (2019) STOA: a bio-inspired based optimization algorithm for industrial engineering problems. Eng Appl Artif Intell 82:148\u2013174","journal-title":"Eng Appl Artif Intell"},{"key":"10767_CR49","doi-asserted-by":"crossref","first-page":"48","DOI":"10.1016\/j.advengsoft.2017.05.014","volume":"114","author":"G Dhiman","year":"2017","unstructured":"Dhiman G, Kumar V (2017) Spotted hyena optimizer: a novel bio-inspired based metaheuristic technique for engineering applications. Adv Eng Softw 114:48\u201370","journal-title":"Adv Eng Softw"},{"key":"10767_CR50","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1016\/j.knosys.2018.11.024","volume":"165","author":"G Dhiman","year":"2019","unstructured":"Dhiman G, Kumar V (2019) Seagull optimization algorithm: theory and its applications for large-scale industrial engineering problems. Knowl-Based Syst 165:169\u2013196","journal-title":"Knowl-Based Syst"},{"issue":"3","key":"10767_CR51","first-page":"1","volume":"46","author":"G Dhrubajyoti","year":"2021","unstructured":"Dhrubajyoti G, Ananda Ra DR, Shibendu Shekhar R (2021) A partition cumunification based genetic-firefly algorithm for single objective optimization. S\u0101dhan\u0101 46(3):1\u201331","journal-title":"S\u0101dhan\u0101"},{"key":"10767_CR52","unstructured":"Dorian Sidea (2024) Improved salp swarm algorithm. MATLAB Central File Exchange. https:\/\/www.mathworks.com\/matlabcentral\/fileexchange\/155984-improved-salp-swarm-algorithm"},{"issue":"2","key":"10767_CR53","doi-asserted-by":"crossref","first-page":"1676","DOI":"10.1016\/j.eswa.2009.06.044","volume":"37","author":"L Dos Santos Coelho","year":"2010","unstructured":"Dos Santos Coelho L (2010) Gaussian quantum-behaved particle swarm optimization approaches for constrained engineering design problems. Expert Syst Appl 37(2):1676\u20131683","journal-title":"Expert Syst Appl"},{"key":"10767_CR54","doi-asserted-by":"crossref","DOI":"10.1016\/j.engappai.2022.104763","volume":"111","author":"S Duman","year":"2022","unstructured":"Duman S, Kahraman HT, Sonmez Y, Guvenc U, Kati M, Aras S (2022) A powerful meta-heuristic search algorithm for solving global optimization and real-world solar photovoltaic parameter estimation problems. Eng Appl Artif Intell 111:104763","journal-title":"Eng Appl Artif Intell"},{"key":"10767_CR55","doi-asserted-by":"crossref","first-page":"105501","DOI":"10.1016\/j.engappai.2022.105501","volume":"117","author":"S Duman","year":"2023","unstructured":"Duman S, Kahraman HT, Kati M (2023) Economical operation of modern power grids incorporating uncertainties of renewable energy sources and load demand using the adaptive fitness-distance balance-based stochastic fractal search algorithm. Eng Appl Artif Intell 117:105501","journal-title":"Eng Appl Artif Intell"},{"issue":"2","key":"10767_CR56","doi-asserted-by":"crossref","first-page":"2125","DOI":"10.1007\/s11227-021-03943-w","volume":"78","author":"H Emami","year":"2022","unstructured":"Emami H (2022) Stock exchange trading optimization algorithm: a human-inspired method for global optimization. J Supercomput 78(2):2125\u20132174","journal-title":"J Supercomput"},{"key":"10767_CR57","doi-asserted-by":"crossref","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","journal-title":"Neurocomputing"},{"key":"10767_CR58","doi-asserted-by":"crossref","first-page":"116022","DOI":"10.1016\/j.enconman.2022.116022","volume":"268","author":"AA Ewees","year":"2022","unstructured":"Ewees AA, Al-qaness MAA, Abualigah L (2022) HBO-LSTM: optimized long short term memory with heap-based optimizer for wind power forecasting. Energy Convers Manage 268:116022","journal-title":"Energy Convers Manage"},{"issue":"8","key":"10767_CR59","doi-asserted-by":"crossref","first-page":"4612","DOI":"10.1002\/int.22733","volume":"37","author":"AE Ezugwu","year":"2022","unstructured":"Ezugwu AE (2022) Advanced discrete firefly algorithm with adaptive mutation-based neighborhood search for scheduling unrelated parallel machines with sequence-dependent setup times. Int J Intell Syst 37(8):4612\u20134653","journal-title":"Int J Intell Syst"},{"key":"10767_CR60","doi-asserted-by":"crossref","first-page":"105190","DOI":"10.1016\/j.knosys.2019.105190","volume":"191","author":"A Faramarzi","year":"2020","unstructured":"Faramarzi A, Heidarinejad M, Stephens B, Mirjalili S (2020) Equilibrium optimizer: a novel optimization algorithm. Knowl-Based Syst 191:105190","journal-title":"Knowl-Based Syst"},{"issue":"3","key":"10767_CR61","doi-asserted-by":"crossref","first-page":"351","DOI":"10.3390\/math10030351","volume":"10","author":"R Farshad","year":"2022","unstructured":"Farshad R, Hamid RS, Mohamed AE, Shaker H, Ali E, Mohammed A, Tamer A (2022) An enhanced grey wolf optimizer with a velocity-aided global search mechanism. Mathematics 10(3):351","journal-title":"Mathematics"},{"key":"10767_CR62","doi-asserted-by":"crossref","first-page":"106734","DOI":"10.1016\/j.asoc.2020.106734","volume":"98","author":"Z Feng","year":"2021","unstructured":"Feng Z, Niu W, Liu S (2021) Cooperation search algorithm: a novel metaheuristic evolutionary intelligence algorithm for numerical optimization and engineering optimization problems. Appl Soft Comput 98:106734","journal-title":"Appl Soft Comput"},{"issue":"5123","key":"10767_CR63","doi-asserted-by":"crossref","first-page":"872","DOI":"10.1126\/science.8346439","volume":"261","author":"S Forrest","year":"1993","unstructured":"Forrest S (1993) Genetic algorithms: principles of natural selection applied to computation. Science 261(5123):872\u2013878","journal-title":"Science"},{"issue":"1","key":"10767_CR64","doi-asserted-by":"crossref","first-page":"17","DOI":"10.1007\/s00366-011-0241-y","volume":"29","author":"AH Gandomi","year":"2013","unstructured":"Gandomi AH, Yang XS, Alavi AH (2013) Cuckoo search algorithm: a metaheuristic approach to solve structural optimization problems. Eng Comput 29(1):17\u201335","journal-title":"Eng Comput"},{"key":"10767_CR65","doi-asserted-by":"crossref","first-page":"106392","DOI":"10.1016\/j.asoc.2020.106392","volume":"93","author":"HN Ghafil","year":"2020","unstructured":"Ghafil HN, J\u00e1rmai K (2020) Dynamic differential annealed optimization: new metaheuristic optimization algorithm for engineering applications. Appl Soft Comput 93:106392","journal-title":"Appl Soft Comput"},{"key":"10767_CR66","doi-asserted-by":"crossref","first-page":"100125","DOI":"10.1016\/j.dajour.2022.100125","volume":"5","author":"M Ghasemi","year":"2022","unstructured":"Ghasemi M, Kadkhoda Mohammadi S, Zare M et al (2022) A new firefly algorithm with improved global exploration and convergence with application to engineering optimization. Decis Anal J 5:100125","journal-title":"Decis Anal J"},{"key":"10767_CR67","doi-asserted-by":"crossref","unstructured":"Gurrola-Ramos J, Hern\u00e0ndez-Aguirre A, Dalmau-Cede\u00f1o O (2020) COLSHADE for real-world single-objective constrained optimization problems. 2020 IEEE Congress on Evolutionary Computation (CEC) 2020, 1\u20138","DOI":"10.1109\/CEC48606.2020.9185583"},{"key":"10767_CR68","doi-asserted-by":"crossref","first-page":"107421","DOI":"10.1016\/j.asoc.2021.107421","volume":"108","author":"U Guvenc","year":"2021","unstructured":"Guvenc U, Duman S, Kahraman HT, Aras S, Kat\u0131 M (2021) Fitness-distance balance based adaptive guided differential evolution algorithm for security-constrained optimal power flow problem incorporating renewable energy sources. Appl Soft Comput 108:107421","journal-title":"Appl Soft Comput"},{"key":"10767_CR69","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2022.108320","volume":"242","author":"FA Hashim","year":"2022","unstructured":"Hashim FA, Hussien AG (2022) Snake optimizer: a novel meta-heuristic optimization algorithm. Knowl-Based Syst 242:108320","journal-title":"Knowl-Based Syst"},{"key":"10767_CR70","doi-asserted-by":"crossref","first-page":"646","DOI":"10.1016\/j.future.2019.07.015","volume":"101","author":"FA Hashim","year":"2019","unstructured":"Hashim FA, Houssein EH, Mabrouk MS, Al-Atabany W, Mirjalili S (2019) Henry gas solubility optimization: a novel physics-based algorithm. Futur Gener Comput Syst 101:646\u2013667","journal-title":"Futur Gener Comput Syst"},{"key":"10767_CR71","doi-asserted-by":"crossref","first-page":"103249","DOI":"10.1016\/j.engappai.2019.103249","volume":"87","author":"V Hayyolalam","year":"2020","unstructured":"Hayyolalam V, Kazem AAP (2020) Black widow optimization algorithm: a novel meta-heuristic approach for solving engineering optimization problems. Eng Appl Artif Intell 87:103249","journal-title":"Eng Appl Artif Intell"},{"key":"10767_CR72","doi-asserted-by":"crossref","unstructured":"Hellwig M, Beyer H (2018) A matrix adaptation evolution strategy for constrained real-parameter optimization. In: 2018 IEEE Congress on Evolutionary Computation (CEC), 2018: 1\u20138","DOI":"10.1109\/CEC.2018.8477950"},{"key":"10767_CR73","doi-asserted-by":"crossref","unstructured":"Holland JH (1992) Adaptation in natural and artificial systems: an introductory analysis with applications to biology, control, and artificial intelligence. MIT Press, pp 211","DOI":"10.7551\/mitpress\/1090.001.0001"},{"key":"10767_CR74","doi-asserted-by":"crossref","first-page":"349","DOI":"10.1016\/j.asoc.2015.07.031","volume":"36","author":"J Huang","year":"2015","unstructured":"Huang J, Gao L, Li X (2015) An effective teaching-learning-based cuckoo search algorithm for parameter optimization problems in structure designing and machining processes. Appl Soft Comput 36:349\u2013356","journal-title":"Appl Soft Comput"},{"key":"10767_CR75","doi-asserted-by":"crossref","first-page":"7665","DOI":"10.1007\/s00521-018-3592-0","volume":"31","author":"K Hussain","year":"2019","unstructured":"Hussain K, Salleh M, Cheng S et al (2019) On the exploration and exploitation in popular swarm-based metaheuristic algorithms. Neural Comput Appl 31:7665\u20137683","journal-title":"Neural Comput Appl"},{"key":"10767_CR76","doi-asserted-by":"crossref","first-page":"112872","DOI":"10.1016\/j.enconman.2020.112872","volume":"213","author":"I Ibrahim","year":"2020","unstructured":"Ibrahim I, Hossain M, Duck B, Nadarajah M (2020) An improved wind driven optimization algorithm for parameters identification of a triple-diode photovoltaic cell model. Energy Convers Manag 213:112872","journal-title":"Energy Convers Manag"},{"key":"10767_CR77","doi-asserted-by":"crossref","first-page":"148","DOI":"10.1016\/j.swevo.2018.02.013","volume":"44","author":"M Jain","year":"2019","unstructured":"Jain M, Singh V, Rani A (2019) A novel nature-inspired algorithm for optimization: squirrel search algorithm. Swarm Evol Comput 44:148\u2013175","journal-title":"Swarm Evol Comput"},{"key":"10767_CR78","doi-asserted-by":"crossref","first-page":"614","DOI":"10.1016\/j.asoc.2015.02.014","volume":"30","author":"JQ James","year":"2015","unstructured":"James JQ, Li VOK (2015) A social spider algorithm for global optimization. Appl Soft Comput 30:614\u2013627","journal-title":"Appl Soft Comput"},{"key":"10767_CR79","doi-asserted-by":"crossref","first-page":"166439","DOI":"10.1016\/j.ijleo.2021.166439","volume":"231","author":"X Jian","year":"2021","unstructured":"Jian X, Zhu Y (2021) Parameters identification of photovoltaic models using modified Rao-1 optimization algorithm. Optik 231:166439","journal-title":"Optik"},{"key":"10767_CR80","doi-asserted-by":"crossref","first-page":"4873","DOI":"10.1007\/s10489-021-02629-3","volume":"52","author":"H Kahraman","year":"2022","unstructured":"Kahraman H, Bakir H, Duman S, Kat\u0131 M, Aras S, Guvenc U (2022) Dynamic FDB selection method and its application: modeling and optimizing of directional overcurrent relays coordination. Appl Intell 52:4873\u20134908","journal-title":"Appl Intell"},{"key":"10767_CR81","doi-asserted-by":"crossref","first-page":"106121","DOI":"10.1016\/j.engappai.2023.106121","volume":"122","author":"HT Kahraman","year":"2023","unstructured":"Kahraman HT, Kat\u0131 M, Aras S, Ta\u015fci D (2023) Development of the Natural Survivor Method (NSM) for designing an updating mechanism in metaheuristic search algorithms. Eng Appl Artif Intell 122:106121","journal-title":"Eng Appl Artif Intell"},{"key":"10767_CR82","doi-asserted-by":"crossref","first-page":"107625","DOI":"10.1016\/j.knosys.2021.107625","volume":"235","author":"W Kaidi","year":"2022","unstructured":"Kaidi W, Khishe M, Mohammadi M (2022) Dynamic levy flight chimp optimization. Knowl-Based Syst 235:107625","journal-title":"Knowl-Based Syst"},{"key":"10767_CR83","doi-asserted-by":"crossref","first-page":"147","DOI":"10.1016\/j.advengsoft.2018.04.007","volume":"121","author":"NA Kallioras","year":"2018","unstructured":"Kallioras NA, Lagaros ND, Avtzis DN (2018) Pity beetle algorithm \u2013 a new metaheuristic inspired by the behavior of bark beetles. Adv Eng Softw 121:147\u2013166","journal-title":"Adv Eng Softw"},{"key":"10767_CR84","doi-asserted-by":"crossref","first-page":"107224","DOI":"10.1016\/j.cie.2021.107224","volume":"156","author":"H Karami","year":"2021","unstructured":"Karami H, Anaraki MV, Farzin S, Mirjalili S (2021) Flow direction algorithm (fda): a novel optimization approach for solving optimization problems. Comput Ind Eng 156:107224","journal-title":"Comput Ind Eng"},{"key":"10767_CR85","doi-asserted-by":"crossref","first-page":"103541","DOI":"10.1016\/j.engappai.2020.103541","volume":"90","author":"S Kaur","year":"2020","unstructured":"Kaur S, Awasthi LK, Sangal AL et al (2020) Tunicate Swarm Algorithm: a new bio-inspired based metaheuristic paradigm for global optimization. Eng Appl Artif Intell 90:103541","journal-title":"Eng Appl Artif Intell"},{"key":"10767_CR86","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1016\/j.compstruc.2016.01.008","volume":"167","author":"A Kaveh","year":"2016","unstructured":"Kaveh A, Bakhshpoori T (2016) Water evaporation optimization: a novel physically inspired optimization algorithm. Comput Struct 167:69\u201385","journal-title":"Comput Struct"},{"key":"10767_CR87","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1016\/j.advengsoft.2017.03.014","volume":"110","author":"A Kaveh","year":"2017","unstructured":"Kaveh A, Dadras A (2017) A novel meta-heuristic optimization algorithm: thermal exchange optimization. Adv Eng Softw 110:69\u201384","journal-title":"Adv Eng Softw"},{"issue":"3","key":"10767_CR88","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):267\u2013289","journal-title":"Acta Mech"},{"issue":"7","key":"10767_CR89","doi-asserted-by":"crossref","first-page":"1129","DOI":"10.1007\/s42107-020-00282-8","volume":"21","author":"A Kaveh","year":"2020","unstructured":"Kaveh A, Seddighian MR, Ghanadpour E (2020a) Black hole mechanics optimization: a novel meta-heuristic algorithm. Asian Journal of Civil Engineering 21(7):1129\u20131149","journal-title":"Asian Journal of Civil Engineering"},{"issue":"4","key":"10767_CR90","doi-asserted-by":"crossref","first-page":"1554","DOI":"10.1108\/EC-05-2020-0235","volume":"38","author":"A Kaveh","year":"2020","unstructured":"Kaveh A, Akbari H, Hosseini SM (2020b) Plasma generation optimization: a new physically-based metaheuristic algorithm for solving constrained optimization problems. Eng Comput 38(4):1554\u20131606","journal-title":"Eng Comput"},{"key":"10767_CR91","doi-asserted-by":"crossref","first-page":"114920","DOI":"10.1016\/j.eswa.2021.114920","volume":"177","author":"S Khalilpourazari","year":"2021","unstructured":"Khalilpourazari S, Doulabi HH, \u00c7ift\u00e7io\u011flu A\u00d6 et al (2021) Gradient-based grey wolf optimizer with Gaussian walk: application in modelling and prediction of the COVID-19 pandemic. Expert Syst Appl 177:114920","journal-title":"Expert Syst Appl"},{"key":"10767_CR92","doi-asserted-by":"crossref","first-page":"78320","DOI":"10.1109\/ACCESS.2022.3193396","volume":"10","author":"K Khelil","year":"2022","unstructured":"Khelil K, Nicolas Z, Naoufel C, Samir BB (2022) Exponential particle swarm optimization for global optimization. IEEE Access 10:78320\u201378344","journal-title":"IEEE Access"},{"key":"10767_CR93","doi-asserted-by":"crossref","first-page":"392","DOI":"10.1016\/j.energy.2019.04.065","volume":"179","author":"\u015e K\u0131lk\u0131\u015f","year":"2019","unstructured":"K\u0131lk\u0131\u015f \u015e, K\u0131lk\u0131\u015f B (2019) An urbanization algorithm for districts with minimized emissions based on urban planning and embodied energy towards net-zero exergy targets. Energy 179:392\u2013406","journal-title":"Energy"},{"key":"10767_CR94","unstructured":"Kumar DS, Zelinka I (2020) A self-adaptive spherical search algorithm for real-world constrained optimization problems. Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion, 2020:13\u201314"},{"key":"10767_CR95","doi-asserted-by":"crossref","unstructured":"Kumar A, Das S, Zelinka I (2020) A modified covariance matrix adaptation evolution strategy for real-world constrained optimization problems. Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion, 2020:11\u201312","DOI":"10.1145\/3377929.3398185"},{"key":"10767_CR96","doi-asserted-by":"crossref","unstructured":"Kundu T, Garg H (2022) A hybrid TLNNABC algorithm for reliability optimization and engineering design problems. Eng Comp 38(6):5251\u20135295","DOI":"10.1007\/s00366-021-01572-8"},{"issue":"3","key":"10767_CR97","first-page":"627","volume":"42","author":"C Li","year":"2011","unstructured":"Li C, Yang S, Nguyen TT (2011) A self-learning particle swarm optimizer for global optimization problems. IEEE Trans Syst Man Cybernetics B Cybern 42(3):627\u2013646","journal-title":"IEEE Trans Syst Man Cybernetics B Cybern"},{"key":"10767_CR98","volume":"270","author":"L Li","year":"2020","unstructured":"Li L, Chang YB, Tseng ML et al (2020a) Wind power prediction using a novel model on wavelet decomposition-support vector machines-improved atomic search algorithm. J Clean Prod 270:121817","journal-title":"J Clean Prod"},{"key":"10767_CR99","doi-asserted-by":"crossref","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 et al (2020c) Slime mould algorithm: a new method for stochastic optimization. Futur Gener Comput Syst 111:300\u2013323","journal-title":"Futur Gener Comput Syst"},{"issue":"4","key":"10767_CR100","doi-asserted-by":"crossref","first-page":"395","DOI":"10.1016\/j.jpse.2021.08.001","volume":"1","author":"Z Li","year":"2021","unstructured":"Li Z, Liang Y, Liao Q, Zhang H (2021) A review of multiproduct pipeline scheduling: from bibliometric analysis to research framework and future research directions. J Pipeline Sci Eng 1(4):395\u2013406","journal-title":"J Pipeline Sci Eng"},{"key":"10767_CR101","doi-asserted-by":"crossref","unstructured":"Li Z, Tam V, Yeung LK (2020b) A study on parameter sensitivity analysis of the virus spread optimization. 2020 IEEE Symposium Series on Computational Intelligence (SSCI). IEEE, 1535\u20131542","DOI":"10.1109\/SSCI47803.2020.9308167"},{"key":"10767_CR102","doi-asserted-by":"crossref","first-page":"336","DOI":"10.1016\/j.solener.2020.06.100","volume":"207","author":"J Liang","year":"2020","unstructured":"Liang J, Qiao K, Yu K, Ge S, Qu B, Xu R, Li K (2020) Parameters estimation of solar photovoltaic models via a self-adaptive ensemble-based differential evolution. Sol Energy 207:336\u2013346","journal-title":"Sol Energy"},{"key":"10767_CR103","doi-asserted-by":"crossref","first-page":"108361","DOI":"10.1016\/j.cie.2022.108361","volume":"171","author":"X Lin","year":"2022","unstructured":"Lin X, Yu X, Li W (2022) A heuristic whale optimization algorithm with niching strategy for global multi-dimensional engineering optimization. Comput Ind Eng 171:108361","journal-title":"Comput Ind Eng"},{"issue":"3","key":"10767_CR104","doi-asserted-by":"crossref","first-page":"450","DOI":"10.1109\/TEVC.2013.2281533","volume":"18","author":"H Liu","year":"2013","unstructured":"Liu H, Gu F, Zhang Q (2013) Decomposition of a multiobjective optimization problem into a number of simple multiobjective subproblems. IEEE Trans Evol Comput 18(3):450\u2013455","journal-title":"IEEE Trans Evol Comput"},{"issue":"10","key":"10767_CR105","first-page":"2148","volume":"46","author":"W Long","year":"2020","unstructured":"Long W, Wu T, Tang M, Xu M, Cai S (2020) Grey wolf optimizer algorithm based on lens imaging learning strategy. Acta Automat Sin 46(10):2148\u20132164","journal-title":"Acta Automat Sin"},{"issue":"3","key":"10767_CR106","doi-asserted-by":"crossref","first-page":"175","DOI":"10.1080\/17445760.2014.889138","volume":"30","author":"M Mandal","year":"2015","unstructured":"Mandal M, Mukhopadhyay A (2015) A novel PSO-based graph-theoretic approach for identifying most relevant and non-redundant gene markers from gene expression data. Int J Parallel Emergent Distrib Syst 30(3):175\u2013192","journal-title":"Int J Parallel Emergent Distrib Syst"},{"issue":"5","key":"10767_CR107","doi-asserted-by":"crossref","first-page":"275","DOI":"10.1016\/0167-6377(84)90061-0","volume":"3","author":"S Martello","year":"1984","unstructured":"Martello S, Pulleyblank WR, Toth, de Werra D (1984) Balanced optimization problems. Oper Res Lett 3(5):275\u2013278","journal-title":"Oper Res Lett"},{"issue":"5","key":"10767_CR108","first-page":"388","volume":"10","author":"R Masadeh","year":"2019","unstructured":"Masadeh R, Mahafzah BA, Sharieh A (2019) Sea lion optimization algorithm. Int J Adv Comput Sci Appl 10(5):388\u2013395","journal-title":"Int J Adv Comput Sci Appl"},{"key":"10767_CR109","doi-asserted-by":"crossref","unstructured":"McFarland D, B\u00f6sser T, Bosser T (1993) Intelligent behavior in animals and robots. Mit Press","DOI":"10.7551\/mitpress\/3830.001.0001"},{"issue":"2","key":"10767_CR110","doi-asserted-by":"crossref","first-page":"114","DOI":"10.1504\/IJBIC.2019.101639","volume":"14","author":"XB Meng","year":"2019","unstructured":"Meng XB, Li HX, Gao XZ (2019) An adaptive reinforcement learning-based bat algorithm for structural design problems. Int J Bio-Inspired Comput 14(2):114\u2013124","journal-title":"Int J Bio-Inspired Comput"},{"key":"10767_CR111","volume":"98","author":"OK Meng","year":"2021","unstructured":"Meng OK, Pauline O, Kiong SC (2021) A carnivorous plant algorithm for solving global optimization problems. Appl Soft Comput J 98:106833","journal-title":"Appl Soft Comput J"},{"key":"10767_CR112","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1016\/j.advengsoft.2015.01.010","volume":"83","author":"S Mirjalili","year":"2015","unstructured":"Mirjalili S (2015a) The ant lion optimizer. Adv Eng Softw 83:80\u201398","journal-title":"Adv Eng Softw"},{"key":"10767_CR113","doi-asserted-by":"crossref","first-page":"228","DOI":"10.1016\/j.knosys.2015.07.006","volume":"89","author":"S Mirjalili","year":"2015","unstructured":"Mirjalili S (2015b) Moth-flame optimization algorithm: a novel nature-inspired heuristic paradigm. Knowl-Based Syst 89:228\u2013249","journal-title":"Knowl-Based Syst"},{"key":"10767_CR114","doi-asserted-by":"crossref","first-page":"120","DOI":"10.1016\/j.knosys.2015.12.022","volume":"96","author":"S Mirjalili","year":"2016","unstructured":"Mirjalili S (2016) SCA: a sine cosine algorithm for solving optimization problems. Knowl-Based Syst 96:120\u2013133","journal-title":"Knowl-Based Syst"},{"key":"10767_CR115","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"},{"key":"10767_CR116","doi-asserted-by":"crossref","first-page":"163","DOI":"10.1016\/j.advengsoft.2017.07.002","volume":"114","author":"S Mirjalili","year":"2017","unstructured":"Mirjalili S, Gandomi AH, Mirjalili SZ, Shahrzad S, Hossam F, Seyed M (2017) Salp swarm algorithm: a bio-inspired optimizer for engineering design problems. Adv Eng Softw 114:163\u2013191","journal-title":"Adv Eng Softw"},{"key":"10767_CR117","doi-asserted-by":"crossref","unstructured":"Mirjalili S (2019) Genetic algorithm. Evolutionary algorithms and neural networks. Springer, Cham, pp 43\u201355","DOI":"10.1007\/978-3-319-93025-1_4"},{"key":"10767_CR118","unstructured":"Moghaddam FF, Moghaddam RF (2012) Cheriet M. Curved space optimization: a random search based on general relativity theory. arXiv preprint arXiv:1208.2214"},{"key":"10767_CR119","doi-asserted-by":"crossref","first-page":"107050","DOI":"10.1016\/j.cie.2020.107050","volume":"152","author":"A Mohammadi-Balani","year":"2021","unstructured":"Mohammadi-Balani A, Nayeri MD, Azar A, Taghizadeh-Yazdi M (2021) Golden eagle optimizer: a nature-inspired metaheuristic algorithm. Comput Ind Eng 152:107050","journal-title":"Comput Ind Eng"},{"key":"10767_CR120","doi-asserted-by":"crossref","first-page":"14701","DOI":"10.1007\/s00521-020-04823-9","volume":"32","author":"H Mohammed","year":"2020","unstructured":"Mohammed H, Rashid T (2020) A novel hybrid GWO with WOA for global numerical optimization and solving pressure vessel design. Neural Comput Appl 32:14701\u201314718","journal-title":"Neural Comput Appl"},{"key":"10767_CR121","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1016\/j.cma.2012.12.009","volume":"256","author":"M Montemurro","year":"2013","unstructured":"Montemurro M, Vincenti A, Vannucci P (2013) The automatic dynamic penalization method (ADP) for handling constraints with genetic algorithms. Comput Methods Appl Mech Engrg 256:70\u201387","journal-title":"Comput Methods Appl Mech Engrg"},{"key":"10767_CR122","doi-asserted-by":"crossref","unstructured":"Moscato P, Cotta C, Mendes A (2004) Memetic algorithms. New optimization techniques in engineering. Springer, Berlin, Heidelberg, pp 53\u201385","DOI":"10.1007\/978-3-540-39930-8_3"},{"key":"10767_CR123","doi-asserted-by":"crossref","first-page":"14297","DOI":"10.1007\/s00500-021-06140-2","volume":"25","author":"MK Naik","year":"2021","unstructured":"Naik MK, Panda R, Abraham A (2021) Adaptive opposition slime mould algorithm. Soft Comput 25:14297\u201314313","journal-title":"Soft Comput"},{"issue":"4","key":"10767_CR124","doi-asserted-by":"crossref","first-page":"3025","DOI":"10.1007\/s00366-021-01438-z","volume":"38","author":"I Naruei","year":"2022","unstructured":"Naruei I, Keynia F (2022) Wild horse optimizer: a new meta-heuristic algorithm for solving engineering optimization problems. Eng with Comput 38(4):3025\u20133056","journal-title":"Eng with Comput"},{"issue":"3","key":"10767_CR125","doi-asserted-by":"crossref","first-page":"1279","DOI":"10.1007\/s00500-021-06401-0","volume":"26","author":"I Naruei","year":"2022","unstructured":"Naruei I, Keynia F, Sabbagh Molahosseini A (2022) Hunter\u2013prey optimization: algorithm and applications. Soft Comput 26(3):1279\u20131314","journal-title":"Soft Comput"},{"key":"10767_CR126","doi-asserted-by":"crossref","first-page":"596","DOI":"10.1016\/j.asoc.2017.06.033","volume":"59","author":"AF Nematollahi","year":"2017","unstructured":"Nematollahi AF, Rahiminejad A, Vahidi B (2017) A novel physical based meta-heuristic optimization method known as lightning attachment procedure optimization. Appl Soft Comput 59:596\u2013621","journal-title":"Appl Soft Comput"},{"issue":"2","key":"10767_CR127","doi-asserted-by":"crossref","first-page":"1117","DOI":"10.1007\/s00500-019-03949-w","volume":"24","author":"AF Nematollahi","year":"2020","unstructured":"Nematollahi AF, Rahiminejad A, Vahidi B (2020) A novel meta-heuristic optimization method based on golden ratio in nature. Soft Comput 24(2):1117\u20131151","journal-title":"Soft Comput"},{"key":"10767_CR128","doi-asserted-by":"crossref","first-page":"514","DOI":"10.1016\/j.matcom.2021.09.014","volume":"192","author":"FK Onay","year":"2022","unstructured":"Onay FK, Aydem\u0131\u0307r SB (2022) Chaotic hunger games search optimization algorithm for global optimization and engineering problems. Math Comput Simul 192:514\u2013536","journal-title":"Math Comput Simul"},{"key":"10767_CR129","doi-asserted-by":"crossref","first-page":"253","DOI":"10.1016\/j.matcom.2022.02.030","volume":"198","author":"BN \u00d6rnek","year":"2022","unstructured":"\u00d6rnek BN, Aydemir SB, D\u00fczenli T et al (2022) A novel version of slime mould algorithm for global optimization and real world engineering problems: enhanced slime mould algorithm. Math Comput Simul 198:253\u2013288","journal-title":"Math Comput Simul"},{"issue":"2","key":"10767_CR130","doi-asserted-by":"crossref","first-page":"908","DOI":"10.1016\/j.amc.2006.01.066","volume":"181","author":"H Pan","year":"2006","unstructured":"Pan H, Wang L, Liu B (2006) Particle swarm optimization for function optimization in noisy environment. Appl Math Comput 181(2):908\u2013919","journal-title":"Appl Math Comput"},{"issue":"2","key":"10767_CR131","doi-asserted-by":"crossref","first-page":"439","DOI":"10.3390\/math11020439","volume":"11","author":"JS Pan","year":"2023","unstructured":"Pan JS, Sun B, Chu SC et al (2023) A parallel compact gannet optimization algorithm for solving engineering optimization problems. Mathematics 11(2):439","journal-title":"Mathematics"},{"issue":"2","key":"10767_CR132","doi-asserted-by":"crossref","first-page":"235","DOI":"10.1023\/A:1016568309421","volume":"1","author":"E Parsopoulos","year":"2002","unstructured":"Parsopoulos E, Vrahatis MN (2002) Recent approaches to global optimization problems through particle swarm optimization. Nat Comput 1(2):235\u2013306","journal-title":"Nat Comput"},{"key":"10767_CR133","doi-asserted-by":"crossref","first-page":"9107547","DOI":"10.1155\/2021\/9107547","volume":"2021","author":"H Peraza-V\u00e1zquez","year":"2021","unstructured":"Peraza-V\u00e1zquez H, Pe\u00f1a-Delgado AF, Echavarr\u00eda-Castillo G et al (2021) A bio-inspired method for engineering design optimization inspired by dingoes hunting strategies. Math Probl Eng 2021:9107547","journal-title":"Math Probl Eng"},{"key":"10767_CR134","doi-asserted-by":"crossref","first-page":"230","DOI":"10.1016\/j.asoc.2018.01.003","volume":"65","author":"TX Pham","year":"2018","unstructured":"Pham TX, Siarry P, Oulhadj H (2018) Integrating fuzzy entropy clustering with an improved PSO for MRI brain image segmentation. Appl Soft Comput 65:230\u2013242","journal-title":"Appl Soft Comput"},{"key":"10767_CR135","doi-asserted-by":"crossref","first-page":"114107","DOI":"10.1016\/j.eswa.2020.114107","volume":"166","author":"D Po\u0142ap","year":"2021","unstructured":"Po\u0142ap D, Wo\u017aniak M (2021) Red fox optimization algorithm. Expert Syst Appl 166:114107","journal-title":"Expert Syst Appl"},{"issue":"1","key":"10767_CR136","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1007\/s11721-007-0002-0","volume":"1","author":"R Poli","year":"2007","unstructured":"Poli R, Kennedy J, Blackwell T (2007) Particle swarm optimization. Swarm Intell 1(1):33\u201357","journal-title":"Swarm Intell"},{"key":"10767_CR137","doi-asserted-by":"crossref","first-page":"118612","DOI":"10.1016\/j.jclepro.2019.118612","volume":"244","author":"W Qiao","year":"2020","unstructured":"Qiao W, Lu H, Zhou G et al (2020) A hybrid algorithm for carbon dioxide emissions forecasting based on improved lion swarm optimizer. J Clean Prod 244:118612","journal-title":"J Clean Prod"},{"key":"10767_CR138","doi-asserted-by":"crossref","first-page":"212233","DOI":"10.1109\/ACCESS.2020.3040136","volume":"8","author":"E Rachdi","year":"2020","unstructured":"Rachdi E, El Merabet Y, Akhtar Z et al (2020) Directional neighborhood topologies based multi-scale quinary pattern for texture classification. IEEE Access 8:212233\u2013212246","journal-title":"IEEE Access"},{"issue":"4","key":"10767_CR139","first-page":"2152","volume":"12","author":"A Ramshanker","year":"2022","unstructured":"Ramshanker A, Chakraborty S (2022) Maiden application of skill optimization algorithm on cascaded multi-level neuro-fuzzy based power system stabilizers for damping oscillations. Int J Renew Energy Res (IJRER) 12(4):2152\u20132167","journal-title":"Int J Renew Energy Res (IJRER)"},{"issue":"3","key":"10767_CR140","doi-asserted-by":"crossref","first-page":"303","DOI":"10.1016\/j.cad.2010.12.015","volume":"43","author":"R Rao","year":"2011","unstructured":"Rao R, Savsani V, Vakharia D (2011) Teaching\u2013learning-based optimization: a novel method for constrained mechanical design optimization problems. Comput Aided Des 43(3):303\u2013315","journal-title":"Comput Aided Des"},{"issue":"12","key":"10767_CR141","doi-asserted-by":"crossref","first-page":"1447","DOI":"10.1080\/0305215X.2011.652103","volume":"44","author":"RV Rao","year":"2012","unstructured":"Rao RV, Savsani VJ, Balic J (2012) Teaching-learning-based optimization algorithm for unconstrained and constrained real-parameter optimization problems. Eng Optim 44(12):1447\u20131462","journal-title":"Eng Optim"},{"issue":"8","key":"10767_CR142","doi-asserted-by":"crossref","first-page":"1229","DOI":"10.1016\/S0098-1354(03)00049-8","volume":"27","author":"J Rejowski","year":"2003","unstructured":"Rejowski J, Pinto JM (2003) Scheduling of a multiproduct pipeline system. Comput Chem Eng 27(8):1229\u20131246","journal-title":"Comput Chem Eng"},{"issue":"9","key":"10767_CR143","doi-asserted-by":"crossref","first-page":"110437","DOI":"10.1016\/j.celrep.2022.110437","volume":"38","author":"Y Ruan","year":"2022","unstructured":"Ruan Y, Li KY, Zheng R et al (2022) Cholinergic neurons in the pedunculopontine nucleus guide reversal learning by signaling the changing reward contingency. Cell Rep 38(9):110437","journal-title":"Cell Rep"},{"key":"10767_CR144","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.knosys.2014.07.025","volume":"75","author":"H Salimi","year":"2015","unstructured":"Salimi H (2015) Stochastic fractal search. a powerful metaheuristic algorithm. Knowl-Based Syst 75:1\u201318","journal-title":"Knowl-Based Syst"},{"key":"10767_CR145","doi-asserted-by":"crossref","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 (2017) Grasshopper optimisation algorithm: theory and application. Adv Eng Softw 105:30\u201347","journal-title":"Adv Eng Softw"},{"issue":"1","key":"10767_CR146","first-page":"49","volume":"15","author":"G Schoenewolf","year":"1990","unstructured":"Schoenewolf G (1990) Emotional contagion: behavioral induction in individuals and groups. Mod Psychoanal 15(1):49\u201361","journal-title":"Mod Psychoanal"},{"key":"10767_CR147","unstructured":"Schwefel HP, Rudolph G (1995) Contemporary evolution strategies. European conference on artificial life. Springer, Berlin, Heidelberg, pp 891\u2013907"},{"issue":"4","key":"10767_CR148","doi-asserted-by":"crossref","first-page":"1095","DOI":"10.1109\/TMAG.2006.871568","volume":"42","author":"JH Seo","year":"2006","unstructured":"Seo JH, Im CH, Heo CG (2006) Multimodal function optimization based on particle swarm optimization. IEEE Trans Magn 42(4):1095\u20131098","journal-title":"IEEE Trans Magn"},{"issue":"6","key":"10767_CR149","doi-asserted-by":"crossref","first-page":"727","DOI":"10.1016\/S0952-1976(02)00013-1","volume":"14","author":"S Sette","year":"2001","unstructured":"Sette S, Boullart L (2001) Genetic programming: principles and applications. Eng Appl Artif Intell 14(6):727\u2013736","journal-title":"Eng Appl Artif Intell"},{"issue":"4","key":"10767_CR150","doi-asserted-by":"crossref","first-page":"2627","DOI":"10.1007\/s00366-022-01604-x","volume":"39","author":"A Seyyedabbasi","year":"2023","unstructured":"Seyyedabbasi A, Kiani F (2023) Sand Cat swarm optimization: a nature-inspired algorithm to solve global optimization problems. Eng Comput 39(4):2627\u20132651","journal-title":"Eng Comput"},{"issue":"3","key":"10767_CR151","doi-asserted-by":"crossref","first-page":"675","DOI":"10.1080\/02564602.2021.1894250","volume":"39","author":"A Sharma","year":"2022","unstructured":"Sharma A, Shoval S, Sharma A, Jitendra KP (2022) Path planning for multiple targets interception by the swarm of UAVs based on swarm intelligence algorithms: a review. IETE Tech Rev 39(3):675\u2013697","journal-title":"IETE Tech Rev"},{"issue":"5","key":"10767_CR152","doi-asserted-by":"crossref","first-page":"255","DOI":"10.1016\/j.ipl.2004.11.003","volume":"93","author":"XH Shi","year":"2005","unstructured":"Shi XH, Liang YC, Lee HP et al (2005) An improved GA and a novel PSO-GA-based hybrid algorithm. Inf Process Lett 93(5):255\u2013261","journal-title":"Inf Process Lett"},{"key":"10767_CR153","doi-asserted-by":"crossref","first-page":"116450","DOI":"10.1016\/j.eswa.2021.116450","volume":"194","author":"S Shitu","year":"2022","unstructured":"Shitu S, Jagdish CB (2022) Mutation-driven grey wolf optimizer with modified search mechanism. Expert Syst Appl 194:116450","journal-title":"Expert Syst Appl"},{"key":"10767_CR154","doi-asserted-by":"crossref","first-page":"106367","DOI":"10.1016\/j.asoc.2020.106367","volume":"93","author":"G Shubham","year":"2020","unstructured":"Shubham G, Kusum D (2020) A memory-based grey wolf optimizer for global optimization tasks. Appl Soft Comput 93:106367","journal-title":"Appl Soft Comput"},{"issue":"1","key":"10767_CR155","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1287\/moor.6.1.19","volume":"6","author":"F Solis","year":"1981","unstructured":"Solis F, Wets J (1981) Minimization by random search techniques. Math Oper Res 6(1):19\u201330","journal-title":"Math Oper Res"},{"key":"10767_CR156","doi-asserted-by":"crossref","first-page":"106425","DOI":"10.1016\/j.knosys.2020.106425","volume":"215","author":"S Song","year":"2021","unstructured":"Song S, Wang P, Heidari AA, Wang M, Zhao X, Chen H, He W, Xu S (2021) Dimension decided Harris Hawks optimization with Gaussian mutation: balance analysis and diversity patterns. Knowl-Based Syst 215:106425","journal-title":"Knowl-Based Syst"},{"key":"10767_CR157","doi-asserted-by":"crossref","first-page":"107499","DOI":"10.1016\/j.ress.2021.107499","volume":"210","author":"X Sun","year":"2021","unstructured":"Sun X, Croke B, Roberts S et al (2021) Comparing methods of randomizing Sobol\u2032 sequences for improving uncertainty of metrics in variance-based global sensitivity estimation. Reliab Eng Syst Saf 210:107499","journal-title":"Reliab Eng Syst Saf"},{"key":"10767_CR158","doi-asserted-by":"crossref","first-page":"578","DOI":"10.1016\/j.ins.2022.06.052","volume":"608","author":"G Tian","year":"2022","unstructured":"Tian G, Fathollahi-Fard AM, Ren Y, Li Z, Jiang X (2022) Multi-objective scheduling of priority-based rescue vehicles to extinguish forest fires using a multi-objective discrete gravitational search algorithm. Inf Sci 608:578\u2013596","journal-title":"Inf Sci"},{"key":"10767_CR159","unstructured":"Trivedi A, Srinivasan D, Biswas N (2018) An improved unified differential evolution algorithm for constrained optimization problems. 2018 IEEE Congress on Evolutionary Computation (CEC), 2018:1\u201310"},{"issue":"1","key":"10767_CR160","doi-asserted-by":"crossref","first-page":"14861","DOI":"10.1038\/s41598-022-19313-2","volume":"12","author":"E Trojovsk\u00e1","year":"2022","unstructured":"Trojovsk\u00e1 E, Dehghani M (2022) A new human-based metahurestic optimization method based on mimicking cooking training. Sci Rep 12(1):14861","journal-title":"Sci Rep"},{"key":"10767_CR161","doi-asserted-by":"crossref","first-page":"49445","DOI":"10.1109\/ACCESS.2022.3172789","volume":"10","author":"E Trojovsk\u00e1","year":"2022","unstructured":"Trojovsk\u00e1 E, Dehghani M, Trojovsk\u00fd P (2022) Zebra optimization algorithm: a new bio-inspired optimization algorithm for solving optimization algorithm. IEEE Access 10:49445\u201349473","journal-title":"IEEE Access"},{"issue":"3","key":"10767_CR162","doi-asserted-by":"crossref","first-page":"855","DOI":"10.3390\/s22030855","volume":"22","author":"P Trojovsk\u00fd","year":"2022","unstructured":"Trojovsk\u00fd P, Dehghani M (2022) Pelican optimization algorithm: a novel nature-inspired algorithm for engineering applications. Sensors 22(3):855","journal-title":"Sensors"},{"issue":"2","key":"10767_CR163","doi-asserted-by":"crossref","first-page":"149","DOI":"10.3390\/biomimetics8020149","volume":"8","author":"P Trojovsk\u00fd","year":"2023","unstructured":"Trojovsk\u00fd P, Dehghani M (2023) Subtraction-average-based optimizer: a new swarm-inspired metaheuristic algorithm for solving optimization problems. Biomimetics 8(2):149","journal-title":"Biomimetics"},{"key":"10767_CR164","doi-asserted-by":"crossref","first-page":"109615","DOI":"10.1016\/j.chaos.2020.109615","volume":"133","author":"AV Tutueva","year":"2020","unstructured":"Tutueva AV, Nepomuceno EG, Karimov AI et al (2020) Adaptive chaotic maps and their application to pseudo-random numbers generation. Chaos Solitons Fractals 133:109615","journal-title":"Chaos Solitons Fractals"},{"key":"10767_CR165","doi-asserted-by":"crossref","first-page":"1995","DOI":"10.1007\/s00521-015-1923-y","volume":"31","author":"GG Wang","year":"2019","unstructured":"Wang GG, Deb S, Cui Z (2019) Monarch butterfly optimization. Neural Comput Appl 31:1995\u20132014","journal-title":"Neural Comput Appl"},{"key":"10767_CR166","volume":"114","author":"L Wang","year":"2022","unstructured":"Wang L, Cao Q, Zhang Z et al (2022a) Artificial rabbits optimization: a new bio-inspired meta-heuristic algorithm for solving engineering optimization problems. Eng Appl Artif Intell 114:105082","journal-title":"Eng Appl Artif Intell"},{"key":"10767_CR167","doi-asserted-by":"crossref","unstructured":"Wang Z, Pan J, Huang K et al (2022b) Hybrid gray wolf optimization and cuckoo search algorithm based on the taguchi theory. Advances in intelligent information hiding and multimedia signal processing. Springer, Singapore, pp 219\u2013228","DOI":"10.1007\/978-981-19-1053-1_20"},{"issue":"1","key":"10767_CR168","first-page":"7","volume":"1","author":"AJ Wilson","year":"2022","unstructured":"Wilson AJ, Pallavi DR, Ramachandran M (2022) A review on memetic algorithms and its developments. Electrical Automation Eng 1(1):7\u201312","journal-title":"Electrical Automation Eng"},{"key":"10767_CR169","doi-asserted-by":"crossref","first-page":"118642","DOI":"10.1016\/j.eswa.2022.118642","volume":"212","author":"Z Xu","year":"2023","unstructured":"Xu Z, Heidari AA, Kuang F et al (2023) Enhanced Gaussian bare-bones grasshopper optimization: mitigating the performance concerns for feature selection. Expert Syst Appl 212:118642","journal-title":"Expert Syst Appl"},{"issue":"1","key":"10767_CR170","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1080\/21642583.2019.1708830","volume":"8","author":"J Xue","year":"2020","unstructured":"Xue J, Shen B (2020) A novel swarm intelligence optimization approach: sparrow search algorithm. Syst Sci Control Eng 8(1):22\u201334","journal-title":"Syst Sci Control Eng"},{"issue":"7","key":"10767_CR171","doi-asserted-by":"crossref","first-page":"7305","DOI":"10.1007\/s11227-022-04959-6","volume":"79","author":"J Xue","year":"2023","unstructured":"Xue J, Shen B (2023) Dung beetle optimizer: a new meta-heuristic algorithm for global optimization. J Supercomput 79(7):7305\u20137336","journal-title":"J Supercomput"},{"issue":"1","key":"10767_CR172","doi-asserted-by":"crossref","first-page":"293","DOI":"10.1016\/j.engappai.2012.01.023","volume":"26","author":"M Yaghini","year":"2013","unstructured":"Yaghini M, Khoshraftar MM, Fallahi M (2013) A hybrid algorithm for artificial neural network training. Eng Appl Artif Intell 26(1):293\u2013301","journal-title":"Eng Appl Artif Intell"},{"issue":"1","key":"10767_CR173","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1007\/s00521-013-1367-1","volume":"24","author":"XS Yang","year":"2014","unstructured":"Yang XS, Deb S (2014) Cuckoo search: recent advances and applications. Neural Comput Appl 24(1):169\u2013174","journal-title":"Neural Comput Appl"},{"key":"10767_CR174","doi-asserted-by":"crossref","first-page":"545","DOI":"10.1016\/j.asoc.2019.03.012","volume":"78","author":"H Yapici","year":"2019","unstructured":"Yapici H, Cetinkaya N (2019) A new meta-heuristic optimizer: pathfinder algorithm. Appl Soft Comput 78:545\u2013568","journal-title":"Appl Soft Comput"},{"issue":"1","key":"10767_CR175","first-page":"24","volume":"3","author":"M Yazdani","year":"2016","unstructured":"Yazdani M, Jolai F (2016) Lion Optimization Algorithm (LOA): a nature-inspired metaheuristic algorithm. J Comput Des Eng 3(1):24\u201336","journal-title":"J Comput Des Eng"},{"key":"10767_CR176","doi-asserted-by":"crossref","first-page":"241","DOI":"10.1016\/j.apenergy.2019.01.008","volume":"237","author":"K Yu","year":"2019","unstructured":"Yu K, Qu B, Yue C, Ge S, Chen X, Liang J (2019) A performance-guided JAYA algorithm for parameters identification of photovoltaic cell and module. Apply Energy 237:241\u2013257","journal-title":"Apply Energy"},{"issue":"8","key":"10767_CR177","doi-asserted-by":"crossref","first-page":"1355","DOI":"10.3390\/math8081355","volume":"8","author":"H Yu","year":"2020","unstructured":"Yu H, Gao Y, Wang L et al (2020) A hybrid particle swarm optimization algorithm enhanced with nonlinear inertial weight and Gaussian mutation for job shop scheduling problems. Mathematics 8(8):1355","journal-title":"Mathematics"},{"key":"10767_CR178","doi-asserted-by":"crossref","DOI":"10.1016\/j.asoc.2019.105583","volume":"85","author":"H Zamani","year":"2019","unstructured":"Zamani H, Nadimi-Shahraki MH, Gandomi AH (2019) CCSA: conscious neighborhood-based crow search algorithm for solving global optimization problems. Appl Soft Comput 85:105583","journal-title":"Appl Soft Comput"},{"key":"10767_CR179","doi-asserted-by":"crossref","first-page":"106559","DOI":"10.1016\/j.cie.2020.106559","volume":"145","author":"K Zervoudakis","year":"2020","unstructured":"Zervoudakis K, Tsafarakis S (2020) A mayfly optimization algorithm. Comput Ind Eng 145:106559","journal-title":"Comput Ind Eng"},{"issue":"5","key":"10767_CR180","doi-asserted-by":"crossref","first-page":"1229","DOI":"10.1007\/s10845-020-01723-6","volume":"33","author":"Y Zhang","year":"2022","unstructured":"Zhang Y, Jin Z (2022) Comprehensive learning Jaya algorithm for engineering design optimization problems. J Intell Manuf 33(5):1229\u20131253","journal-title":"J Intell Manuf"},{"key":"10767_CR181","doi-asserted-by":"crossref","first-page":"464","DOI":"10.1016\/j.apm.2018.06.036","volume":"63","author":"J Zhang","year":"2018","unstructured":"Zhang J, Xiao M, Gao L, Pan Q (2018) Queuing search algorithm: a novel metaheuristic algorithm for solving engineering optimization problems. Appl Math Model 63:464\u2013490","journal-title":"Appl Math Model"},{"issue":"11","key":"10767_CR182","doi-asserted-by":"crossref","first-page":"1800","DOI":"10.3390\/sym12111800","volume":"12","author":"M Zhang","year":"2020","unstructured":"Zhang M, Long D, Qin T et al (2020) A chaotic hybrid butterfly optimization algorithm with particle swarm optimization for high-dimensional optimization problems. Symmetry 12(11):1800","journal-title":"Symmetry"},{"key":"10767_CR183","volume":"95","author":"Q Zhang","year":"2021","unstructured":"Zhang Q, Li H, Liu Y et al (2021a) A new quantum particle swarm optimization algorithm for controller placement problem in software-defined networking. Comput Electr Eng 95:107456","journal-title":"Comput Electr Eng"},{"key":"10767_CR184","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2021.107555","volume":"233","author":"Y Zhang","year":"2021","unstructured":"Zhang Y, Chi A, Mirjalili S (2021b) Enhanced Jaya algorithm: a simple but efficient optimization method for constrained engineering design problems. Knowl-Based Syst 233:107555","journal-title":"Knowl-Based Syst"},{"key":"10767_CR185","doi-asserted-by":"crossref","unstructured":"Zhang H, Liu T, Ye X, Heidari AA, Liang G, Chen H, Pan Z (2022) Differential evolution-assisted salp swarm algorithm with chaotic structure for real-world problems. Eng Comput:1\u201335","DOI":"10.1007\/s00366-022-01609-6"},{"key":"10767_CR186","doi-asserted-by":"crossref","first-page":"73182","DOI":"10.1109\/ACCESS.2019.2918753","volume":"7","author":"W Zhao","year":"2019","unstructured":"Zhao W, Wang L, Zhang Z (2019) Supply-demand-based optimization: a novel economics-inspired algorithm for global optimization. IEEE Access 7:73182\u201373206","journal-title":"IEEE Access"},{"key":"10767_CR187","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2022.109215","volume":"251","author":"C Zhong","year":"2022","unstructured":"Zhong C, Li G, Meng Z (2022) Beluga whale optimization: a novel nature-inspired metaheuristic algorithm. Knowl-Based Syst 251:109215","journal-title":"Knowl-Based Syst"},{"key":"10767_CR188","doi-asserted-by":"crossref","first-page":"4542","DOI":"10.1109\/ACCESS.2020.3047912","volume":"9","author":"F Zitouni","year":"2020","unstructured":"Zitouni F, Harous S, Maamri R (2020) The solar system algorithm: a novel metaheuristic method for global optimization. IEEE Access 9:4542\u20134565","journal-title":"IEEE Access"},{"key":"10767_CR189","doi-asserted-by":"publisher","DOI":"10.1007\/s13369-021-06208-z","author":"F Zitouni","year":"2021","unstructured":"Zitouni F, Harous S, Belkeram A, Hammou LEB (2021) The Archerfish hunting optimizer: a novel metaheuristic algorithm for global optimization. Arab J Sci Eng. https:\/\/doi.org\/10.1007\/s13369-021-06208-z","journal-title":"Arab J Sci Eng"}],"container-title":["Artificial Intelligence Review"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10462-024-10767-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10462-024-10767-6\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10462-024-10767-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,18]],"date-time":"2024-11-18T13:33:26Z","timestamp":1731936806000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10462-024-10767-6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,5,9]]},"references-count":189,"journal-issue":{"issue":"6","published-online":{"date-parts":[[2024,6]]}},"alternative-id":["10767"],"URL":"https:\/\/doi.org\/10.1007\/s10462-024-10767-6","relation":{},"ISSN":["1573-7462"],"issn-type":[{"value":"1573-7462","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,5,9]]},"assertion":[{"value":"18 April 2024","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"9 May 2024","order":2,"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"}}],"article-number":"139"}}