{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,10]],"date-time":"2026-02-10T16:44:53Z","timestamp":1770741893913,"version":"3.49.0"},"reference-count":133,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2021,9,21]],"date-time":"2021-09-21T00:00:00Z","timestamp":1632182400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2021,9,21]],"date-time":"2021-09-21T00:00:00Z","timestamp":1632182400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Engineering with Computers"],"published-print":{"date-parts":[[2023,4]]},"DOI":"10.1007\/s00366-021-01487-4","type":"journal-article","created":{"date-parts":[[2021,9,21]],"date-time":"2021-09-21T06:03:40Z","timestamp":1632204220000},"page":"1183-1228","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":37,"title":["An improved Chaotic Harris Hawks Optimizer for solving numerical and engineering optimization problems"],"prefix":"10.1007","volume":"39","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9307-1232","authenticated-orcid":false,"given":"Dinesh","family":"Dhawale","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Vikram Kumar","family":"Kamboj","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Priyanka","family":"Anand","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,9,21]]},"reference":[{"key":"1487_CR1","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 (2014) Grey wolf optimizer. Adv Eng Softw 69:46\u201361. https:\/\/doi.org\/10.1016\/j.advengsoft.2013.12.007","journal-title":"Adv Eng Softw"},{"key":"1487_CR2","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 (2006) Ant colony optimization. IEEE Comput Intell Mag 1:28\u201339. https:\/\/doi.org\/10.1109\/MCI.2006.329691","journal-title":"IEEE Comput Intell Mag"},{"key":"1487_CR3","doi-asserted-by":"publisher","first-page":"1942","DOI":"10.1109\/ICNN.1995.488968","volume-title":"Proceedings of IEEE international conference of neural network","author":"J Kennedy","year":"1995","unstructured":"Kennedy J, Eberhart RC (1995) Particle swarm optimization. In: Perth A (ed) Proceedings of IEEE international conference of neural network. Springer, Cham, pp 1942\u20131948"},{"key":"1487_CR4","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1007\/s10462-012-9328-0","volume":"42","author":"D Karaboga","year":"2014","unstructured":"Karaboga D, Gorkemli B, Ozturk C, Karaboga N (2014) A comprehensive survey: artificial bee colony (ABC) algorithm and applications. Artif Intell Rev 42:21\u201357. https:\/\/doi.org\/10.1007\/s10462-012-9328-0","journal-title":"Artif Intell Rev"},{"key":"1487_CR5","doi-asserted-by":"publisher","first-page":"65","DOI":"10.1007\/978-3-642-12538-6_6","volume-title":"Nature inspired ooperative strategies for optimization (NICSO 2010)","author":"XS Yang","year":"2010","unstructured":"Yang XS (2010) A new metaheuristic bat-inspired algorithm. Nature inspired ooperative strategies for optimization (NICSO 2010). Springer, Cham, p 65"},{"key":"1487_CR6","doi-asserted-by":"publisher","first-page":"228","DOI":"10.1016\/j.knosys.2015.07.006","volume":"89","author":"S Mirjalili","year":"2015","unstructured":"Mirjalili S (2015) Moth-flame optimization algorithm: a novel nature-inspired heuristic paradigm. Knowl -Based Syst 89:228\u2013249. https:\/\/doi.org\/10.1016\/j.knosys.2015.07.006","journal-title":"Knowl -Based Syst"},{"key":"1487_CR7","doi-asserted-by":"publisher","first-page":"4831","DOI":"10.1016\/j.cnsns.2012.05.010","volume":"17","author":"AH Gandomi","year":"2012","unstructured":"Gandomi AH, Alavi AH (2012) Krill herd: a new bio-inspired optimization algorithm. Commun Nonlinear Sci Numer Simul 17:4831\u20134845. https:\/\/doi.org\/10.1016\/j.cnsns.2012.05.010","journal-title":"Commun Nonlinear Sci Numer Simul"},{"key":"1487_CR8","doi-asserted-by":"publisher","first-page":"151","DOI":"10.1016\/j.compstruc.2012.07.010","volume":"110\u2013111","author":"H Eskandar","year":"2012","unstructured":"Eskandar H, Sadollah A, Bahreininejad A, Hamdi M (2012) Water cycle algorithm: a novel metaheuristic optimization method for solving constrained engineering optimization problems. Comput Struct 110\u2013111:151\u2013166. https:\/\/doi.org\/10.1016\/j.compstruc.2012.07.010","journal-title":"Comput Struct"},{"key":"1487_CR9","doi-asserted-by":"publisher","first-page":"1867","DOI":"10.1007\/s00521-013-1433-8","volume":"24","author":"X Li","year":"2014","unstructured":"Li X, Zhang J, Yin M (2014) Animal migration optimization: an optimization algorithm inspired by animal migration behavior. Neural Comput Appl 24:1867\u20131877. https:\/\/doi.org\/10.1007\/s00521-013-1433-8","journal-title":"Neural Comput Appl"},{"key":"1487_CR10","doi-asserted-by":"publisher","first-page":"4661","DOI":"10.1109\/CEC.2007.4425083","volume":"2007","author":"E Atashpaz-Gargari","year":"2007","unstructured":"Atashpaz-Gargari E, Lucas C (2007) Imperialist competitive algorithm: an algorithm for optimization inspired by imperialistic competition, 2007 IEEE Congr. Evol Comput CEC 2007:4661\u20134667. https:\/\/doi.org\/10.1109\/CEC.2007.4425083","journal-title":"Evol Comput CEC"},{"key":"1487_CR11","doi-asserted-by":"publisher","first-page":"444","DOI":"10.1109\/TPAS.1983.317714","volume":"102","author":"AI Cohen","year":"1983","unstructured":"Cohen AI, Yoshimura M (1983) A branch-and-bound algorithm for unit commitment. IEEE Trans Power Appar Syst 102:444\u2013451","journal-title":"IEEE Trans Power Appar Syst"},{"key":"1487_CR12","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 (2019) Harris Hawks optimization: algorithm and applications. Futur Gener Comput Syst 97:849\u2013872. https:\/\/doi.org\/10.1016\/j.future.2019.02.028","journal-title":"Futur Gener Comput Syst"},{"key":"1487_CR13","doi-asserted-by":"publisher","first-page":"83","DOI":"10.1109\/59.485989","volume":"11","author":"SA Kazarlis","year":"1996","unstructured":"Kazarlis SA, Bakirtzis AG, Petridis V (1996) A genetic algorithm solution to the unit commitment problem. IEEE Trans Power Syst 11:83\u201392. https:\/\/doi.org\/10.1109\/59.485989","journal-title":"IEEE Trans Power Syst"},{"key":"1487_CR14","doi-asserted-by":"publisher","first-page":"341","DOI":"10.1023\/A:1008202821328","volume":"11","author":"R Storn","year":"1997","unstructured":"Storn R, Price K (1997) Differential evolution-a simple and efficient heuristic for global optimization over continuous spaces. J Glob Optim 11:341\u2013359","journal-title":"J Glob Optim"},{"key":"1487_CR15","doi-asserted-by":"publisher","first-page":"A3","DOI":"10.1051\/smdo\/2019002","volume":"10","author":"H Hamdani","year":"2019","unstructured":"Hamdani H, Radi B, El Hami A (2019) Optimization of solder joints in embedded mechatronic systems via Kriging-assisted CMA-ES algorithm. Int J Simul Multidiscip Des Optim 10:A3. https:\/\/doi.org\/10.1051\/smdo\/2019002","journal-title":"Int J Simul Multidiscip Des Optim"},{"key":"1487_CR16","doi-asserted-by":"publisher","first-page":"2232","DOI":"10.1016\/j.ins.2009.03.004","volume":"179","author":"E Rashedi","year":"2009","unstructured":"Rashedi E, Nezamabadi-pour H, Saryazdi S (2009) GSA: a gravitational search algorithm. Inf Sci (Ny) 179:2232\u20132248. https:\/\/doi.org\/10.1016\/j.ins.2009.03.004","journal-title":"Inf Sci (Ny)"},{"key":"1487_CR17","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46173-1","volume-title":"Advances in metaheuristic algorithms for optimal design of structures","author":"A Kaveh","year":"2016","unstructured":"Kaveh A (2016) Advances in metaheuristic algorithms for optimal design of structures, 2nd edn. Springer, Cham. https:\/\/doi.org\/10.1007\/978-3-319-46173-1","edition":"2"},{"key":"1487_CR18","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 (2016) Multi-verse optimizer: a nature-inspired algorithm for global optimization. Neural Comput Appl 27:495\u2013513. https:\/\/doi.org\/10.1007\/s00521-015-1870-7","journal-title":"Neural Comput Appl"},{"key":"1487_CR19","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 (2016) SCA: a sine cosine algorithm for solving optimization problems. Knowl-Based Syst 96:120\u2013133. https:\/\/doi.org\/10.1016\/j.knosys.2015.12.022","journal-title":"Knowl-Based Syst"},{"key":"1487_CR20","doi-asserted-by":"publisher","first-page":"43","DOI":"10.4114\/ia.v7i19.714","volume":"7","author":"F Glover","year":"2003","unstructured":"Glover F, Meli\u00e1n B (2003) Tabu search. Intel Artif 7:43\u201357. https:\/\/doi.org\/10.4114\/ia.v7i19.714","journal-title":"Intel Artif"},{"key":"1487_CR21","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/2193-1801-2-130","volume":"2","author":"SC Satapathy","year":"2013","unstructured":"Satapathy SC, Naik A, Parvathi K (2013) A teaching learning based optimization based on orthogonal design for solving global optimization problems. Springerplus 2:1\u201312. https:\/\/doi.org\/10.1186\/2193-1801-2-130","journal-title":"Springerplus"},{"key":"1487_CR22","doi-asserted-by":"publisher","first-page":"79","DOI":"10.1007\/s10489-016-0825-8","volume":"46","author":"S Mirjalili","year":"2017","unstructured":"Mirjalili S, Jangir P, Saremi S (2017) Multi-objective ant lion optimizer: a multi-objective optimization algorithm for solving engineering problems. Appl Intell 46:79\u201395. https:\/\/doi.org\/10.1007\/s10489-016-0825-8","journal-title":"Appl Intell"},{"key":"1487_CR23","doi-asserted-by":"publisher","first-page":"1077","DOI":"10.1007\/s00521-014-1597-x","volume":"25","author":"S Saremi","year":"2014","unstructured":"Saremi S, Mirjalili S, Lewis A (2014) Biogeography-based optimisation with chaos. Neural Comput Appl 25:1077\u20131097. https:\/\/doi.org\/10.1007\/s00521-014-1597-x","journal-title":"Neural Comput Appl"},{"key":"1487_CR24","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, Abd Elaziz M, Gandomi AH (2021) The arithmetic optimization algorithm. Comput Methods Appl Mech Eng 376:113609. https:\/\/doi.org\/10.1016\/j.cma.2020.113609","journal-title":"Comput Methods Appl Mech Eng"},{"key":"1487_CR25","doi-asserted-by":"publisher","first-page":"1531","DOI":"10.1007\/s10489-020-01893-z","volume":"51","author":"FA Hashim","year":"2021","unstructured":"Hashim FA, Hussain K, Houssein EH, Mabrouk MS, Al-Atabany W (2021) Archimedes optimization algorithm: a new metaheuristic algorithm for solving optimization problems. Appl Intell 51:1531\u20131551. https:\/\/doi.org\/10.1007\/s10489-020-01893-z","journal-title":"Appl Intell"},{"key":"1487_CR26","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1111\/exsy.12642","volume":"38","author":"K Hu","year":"2021","unstructured":"Hu K, Jiang H, Ji CG, Pan Z (2021) A modified butterfly optimization algorithm: an adaptive algorithm for global optimization and the support vector machine. Expert Syst 38:1\u201318. https:\/\/doi.org\/10.1111\/exsy.12642","journal-title":"Expert Syst"},{"key":"1487_CR27","doi-asserted-by":"publisher","DOI":"10.1007\/s00366-021-01371-1","volume-title":"Kamboj, hSMA-PS: a novel memetic approach for numerical and engineering design challenges","author":"A Bala Krishna","year":"2021","unstructured":"Bala Krishna A, Saxena S, V.K, (2021) Kamboj, hSMA-PS: a novel memetic approach for numerical and engineering design challenges. Springer, London. https:\/\/doi.org\/10.1007\/s00366-021-01371-1"},{"key":"1487_CR28","doi-asserted-by":"publisher","DOI":"10.1016\/j.cie.2021.107250","volume":"157","author":"L Abualigah","year":"2021","unstructured":"Abualigah L, Yousri D, Abd Elaziz M, Ewees AA, Al-qaness MAA, Gandomi AH (2021) Aquila optimizer: a novel meta-heuristic optimization algorithm. Comput Ind Eng 157:107250. https:\/\/doi.org\/10.1016\/j.cie.2021.107250","journal-title":"Comput Ind Eng"},{"key":"1487_CR29","doi-asserted-by":"publisher","first-page":"71104","DOI":"10.1109\/access.2021.3077616","volume":"9","author":"Z Xu","year":"2021","unstructured":"Xu Z, Gui W, Heidari AA, Liang G, Chen H, Wu C, Turabieh H, Mafarja M (2021) Spiral motion mode embedded grasshopper optimization algorithm: design and analysis. IEEE Access 9:71104\u201371132. https:\/\/doi.org\/10.1109\/access.2021.3077616","journal-title":"IEEE Access"},{"key":"1487_CR30","doi-asserted-by":"publisher","DOI":"10.1016\/j.energy.2021.120617","volume":"229","author":"M Neshat","year":"2021","unstructured":"Neshat M, Nezhad MM, Abbasnejad E, Mirjalili S, Groppi D, Heydari A, Tjernberg LB, Astiaso Garcia D, Alexander B, Shi Q, Wagner M (2021) Wind turbine power output prediction using a new hybrid neuro-evolutionary method. Energy 229:120617. https:\/\/doi.org\/10.1016\/j.energy.2021.120617","journal-title":"Energy"},{"key":"1487_CR31","doi-asserted-by":"publisher","DOI":"10.1080\/01430750.2021.1888798","author":"A Kaur","year":"2021","unstructured":"Kaur A, Singh L, Dhillon JS (2021) Modified Krill Herd algorithm for constrained economic load dispatch problem. Int J Ambient Energy. https:\/\/doi.org\/10.1080\/01430750.2021.1888798","journal-title":"Int J Ambient Energy"},{"key":"1487_CR32","doi-asserted-by":"publisher","DOI":"10.1186\/s43067-020-00026-3","author":"A Nandi","year":"2021","unstructured":"Nandi A, Kamboj VK (2021) A meliorated Harris Hawks Optimizer for combinatorial unit commitment problem with photovoltaic applications. J Electr Syst Inf Technol. https:\/\/doi.org\/10.1186\/s43067-020-00026-3","journal-title":"J Electr Syst Inf Technol"},{"key":"1487_CR33","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2021.114864","volume":"177","author":"Y Yang","year":"2021","unstructured":"Yang Y, Chen H, Heidari AA, Gandomi AH (2021) Hunger games search: Visions, conception, implementation, deep analysis, perspectives, and towards performance shifts. Expert Syst Appl 177:114864. https:\/\/doi.org\/10.1016\/j.eswa.2021.114864","journal-title":"Expert Syst Appl"},{"key":"1487_CR34","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-16-0662-5_5","author":"E Osaba","year":"2021","unstructured":"Osaba E, Yang X-S (2021) Soccer-inspired metaheuristics: systematic review of recent research and applications. Appl Optim Swarm Intell. https:\/\/doi.org\/10.1007\/978-981-16-0662-5_5","journal-title":"Appl Optim Swarm Intell"},{"key":"1487_CR35","doi-asserted-by":"publisher","DOI":"10.1007\/s00366-020-01120-w","volume-title":"HMPA: an innovative hybrid multi-population algorithm based on artificial ecosystem-based and Harris Hawks optimization algorithms for engineering problems","author":"S Barshandeh","year":"2020","unstructured":"Barshandeh S, Piri F, Sangani SR (2020) HMPA: an innovative hybrid multi-population algorithm based on artificial ecosystem-based and Harris Hawks optimization algorithms for engineering problems. Springer, London. https:\/\/doi.org\/10.1007\/s00366-020-01120-w"},{"key":"1487_CR36","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2020.03.055","author":"S Li","year":"2020","unstructured":"Li S, Chen H, Wang M, Heidari AA, Mirjalili S (2020) Slime mould algorithm: a new method for stochastic optimization. Futur Gener Comput Syst. https:\/\/doi.org\/10.1016\/j.future.2020.03.055","journal-title":"Futur Gener Comput Syst"},{"key":"1487_CR37","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2020.113377","volume":"152","author":"A Faramarzi","year":"2020","unstructured":"Faramarzi A, Heidarinejad M, Mirjalili S, Gandomi AH (2020) Marine predators algorithm: a nature-inspired metaheuristic. Expert Syst Appl 152:113377. https:\/\/doi.org\/10.1016\/j.eswa.2020.113377","journal-title":"Expert Syst Appl"},{"key":"1487_CR38","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2019.02.028","author":"AA Heidari","year":"2019","unstructured":"Heidari AA, Mirjalili S, Faris H, Aljarah I, Mafarja M, Chen H (2019) Harris Hawks optimization: algorithm and applications. Futur Gener Comput Syst. https:\/\/doi.org\/10.1016\/j.future.2019.02.028","journal-title":"Futur Gener Comput Syst"},{"key":"1487_CR39","doi-asserted-by":"publisher","DOI":"10.1016\/j.swevo.2019.01.003","author":"X Chen","year":"2019","unstructured":"Chen X, Tianfield H, Li K, SC, (2019) Self-adaptive differential artificial bee colony algorithm for global optimization problems. Swarm Evol Comput. https:\/\/doi.org\/10.1016\/j.swevo.2019.01.003","journal-title":"Swarm Evol Comput"},{"key":"1487_CR40","doi-asserted-by":"publisher","first-page":"20","DOI":"10.1016\/j.engappai.2019.01.001","volume":"80","author":"S Shadravan","year":"2019","unstructured":"Shadravan S, Naji HR, Bardsiri VK (2019) The Sailfish Optimizer: a novel nature-inspired metaheuristic algorithm for solving constrained engineering optimization problems. Eng Appl Artif Intell 80:20\u201334. https:\/\/doi.org\/10.1016\/j.engappai.2019.01.001","journal-title":"Eng Appl Artif Intell"},{"key":"1487_CR41","doi-asserted-by":"crossref","unstructured":"Pierezan J (2018) Coyote optimization algorithm\u202f: a new metaheuristic for global optimization problems. In: 2018 IEEE Congress on Evolutionary Computation, pp 1\u20138","DOI":"10.1109\/CEC.2018.8477769"},{"key":"1487_CR42","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-13-3708-6","volume-title":"Barnacles mating optimizer algorithm for optimization mohd","author":"MH Sulaiman","year":"2019","unstructured":"Sulaiman MH, Mustaffa Z, Saari MM, Daniyal H, Mohamad AJ, Othman MR (2019) Barnacles mating optimizer algorithm for optimization mohd. Springer, Singapore. https:\/\/doi.org\/10.1007\/978-981-13-3708-6"},{"key":"1487_CR43","doi-asserted-by":"publisher","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, Saremi S, Faris H, Mirjalili SM (2017) Salp swarm algorithm: a bio-inspired optimizer for engineering design problems. Adv Eng Softw 114:163\u2013191. https:\/\/doi.org\/10.1016\/j.advengsoft.2017.07.002","journal-title":"Adv Eng Softw"},{"key":"1487_CR44","doi-asserted-by":"publisher","DOI":"10.1016\/j.compchemeng.2017.01.046","author":"A Tabari","year":"2017","unstructured":"Tabari A, Ahmad A (2017) Accept e us cr t. Comput Chem Eng. https:\/\/doi.org\/10.1016\/j.compchemeng.2017.01.046","journal-title":"Comput Chem Eng"},{"key":"1487_CR45","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 (2017) Grasshopper optimisation algorithm: theory and application. Adv Eng Softw 105:30\u201347. https:\/\/doi.org\/10.1016\/j.advengsoft.2017.01.004","journal-title":"Adv Eng Softw"},{"key":"1487_CR46","doi-asserted-by":"publisher","first-page":"1586","DOI":"10.1016\/j.jestch.2017.11.001","volume":"20","author":"N Singh","year":"2017","unstructured":"Singh N, Singh SB (2017) A novel hybrid GWO-SCA approach for optimization problems. Eng Sci Technol an Int J 20:1586\u20131601. https:\/\/doi.org\/10.1016\/j.jestch.2017.11.001","journal-title":"Eng Sci Technol an Int J"},{"key":"1487_CR47","first-page":"340","volume":"7","author":"NB Gohil","year":"2017","unstructured":"Gohil NB, Dwivedi VV (2017) A review on lion optimization\u202f: nature inspired evolutionary algorithm. Int J Adv Manag Technol Eng Sci 7:340\u2013352","journal-title":"Int J Adv Manag Technol Eng Sci"},{"key":"1487_CR48","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 (2016) The whale optimization algorithm. Adv Eng Softw 95:51\u201367. https:\/\/doi.org\/10.1016\/j.advengsoft.2016.01.008","journal-title":"Adv Eng Softw"},{"key":"1487_CR49","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2015.06.083","author":"B Gray","year":"2015","unstructured":"Gray B (2015) W. optimization, author\u2019 s accepted manuscript binary gray wolf optimization approaches for feature selection. Neurocomputing. https:\/\/doi.org\/10.1016\/j.neucom.2015.06.083","journal-title":"Neurocomputing"},{"key":"1487_CR50","doi-asserted-by":"crossref","unstructured":"Shahriar MS, Rana MJ, Asif MA, Hasan MM, Hawlader MM (2015) Optimization of Unit Commitment Problem for wind-thermal generation using Fuzzy optimization technique. In 2015 International conference on advances in electrical engineering (ICAEE).  IEEE, pp 88\u201392","DOI":"10.1109\/ICAEE.2015.7506803"},{"key":"1487_CR51","doi-asserted-by":"publisher","first-page":"3860","DOI":"10.1016\/j.apm.2015.10.052","volume":"40","author":"L Huang","year":"2016","unstructured":"Huang L, Ding S, Yu S, Wang J, Lu K (2016) Chaos-enhanced Cuckoo search optimization algorithms for global optimization. Appl Math Model 40:3860\u20133875. https:\/\/doi.org\/10.1016\/j.apm.2015.10.052","journal-title":"Appl Math Model"},{"key":"1487_CR52","doi-asserted-by":"publisher","first-page":"340","DOI":"10.1016\/j.energy.2014.06.026","volume":"73","author":"M Ghasemi","year":"2014","unstructured":"Ghasemi M, Ghavidel S, Akbari E, Vahed AA (2014) Solving non-linear, non-smooth and non-convex optimal power flow problems using chaotic invasive weed optimization algorithms based on chaos. Energy 73:340\u2013353. https:\/\/doi.org\/10.1016\/j.energy.2014.06.026","journal-title":"Energy"},{"key":"1487_CR53","doi-asserted-by":"publisher","first-page":"98","DOI":"10.1016\/j.compstruc.2014.03.007","volume":"139","author":"MY Cheng","year":"2014","unstructured":"Cheng MY, Prayogo D (2014) Symbiotic organisms search: a new metaheuristic optimization algorithm. Comput Struct 139:98\u2013112. https:\/\/doi.org\/10.1016\/j.compstruc.2014.03.007","journal-title":"Comput Struct"},{"key":"1487_CR54","doi-asserted-by":"publisher","first-page":"17","DOI":"10.1016\/j.ins.2014.02.123","volume":"274","author":"GG Wang","year":"2014","unstructured":"Wang GG, Guo L, Gandomi AH, Hao GS, Wang H (2014) Chaotic Krill Herd algorithm. Inf Sci (Ny) 274:17\u201334. https:\/\/doi.org\/10.1016\/j.ins.2014.02.123","journal-title":"Inf Sci (Ny)"},{"key":"1487_CR55","doi-asserted-by":"publisher","first-page":"1168","DOI":"10.1016\/j.isatra.2014.03.018","volume":"53","author":"AH Gandomi","year":"2014","unstructured":"Gandomi AH (2014) Interior search algorithm (ISA): a novel approach for global optimization. ISA Trans 53:1168\u20131183. https:\/\/doi.org\/10.1016\/j.isatra.2014.03.018","journal-title":"ISA Trans"},{"key":"1487_CR56","doi-asserted-by":"publisher","DOI":"10.1109\/INCoS.2014.55","author":"S Mohseni","year":"2014","unstructured":"Mohseni S, Gholami R, Zarei N, Zadeh AR (2014) Competition over resources: a new optimization algorithm based on animals behavioral ecology. Proc Int Conf Intell Netw Collab Syst. https:\/\/doi.org\/10.1109\/INCoS.2014.55","journal-title":"Proc Int Conf Intell Netw Collab Syst"},{"key":"1487_CR57","doi-asserted-by":"publisher","first-page":"6676","DOI":"10.1016\/j.eswa.2014.05.009","volume":"41","author":"M Ghaemi","year":"2014","unstructured":"Ghaemi M, Feizi-Derakhshi MR (2014) Forest optimization algorithm. Expert Syst Appl 41:6676\u20136687. https:\/\/doi.org\/10.1016\/j.eswa.2014.05.009","journal-title":"Expert Syst Appl"},{"key":"1487_CR58","doi-asserted-by":"publisher","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. https:\/\/doi.org\/10.1016\/j.knosys.2014.07.025","journal-title":"Knowl-Based Syst"},{"key":"1487_CR59","doi-asserted-by":"publisher","first-page":"510","DOI":"10.1016\/S1665-6423(13)71558-X","volume":"11","author":"HC Kuo","year":"2013","unstructured":"Kuo HC, Lin CH (2013) Cultural evolution algorithm for global optimizations and its applications. J Appl Res Technol 11:510\u2013522. https:\/\/doi.org\/10.1016\/S1665-6423(13)71558-X","journal-title":"J Appl Res Technol"},{"key":"1487_CR60","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-021-05720-5","volume-title":"Harris hawks optimization: a comprehensive review of recent variants and applications","author":"HM Alabool","year":"2021","unstructured":"Alabool HM, Alarabiat D, Abualigah L, Heidari AA (2021) Harris hawks optimization: a comprehensive review of recent variants and applications. Springer, London. https:\/\/doi.org\/10.1007\/s00521-021-05720-5"},{"key":"1487_CR61","doi-asserted-by":"publisher","first-page":"725","DOI":"10.3139\/120.111377","volume":"61","author":"AR Y\u0131ld\u0131z","year":"2019","unstructured":"Y\u0131ld\u0131z AR, Y\u0131ld\u0131z BS, Sait SM, Li X (2019) The Harris hawks, grasshopper and multi-verse optimization algorithms for the selection of optimal machining parameters in manufacturing operations. Mater Test 61:725\u2013733. https:\/\/doi.org\/10.3139\/120.111377","journal-title":"Mater Test"},{"key":"1487_CR62","doi-asserted-by":"publisher","first-page":"1409","DOI":"10.1007\/s00366-019-00892-0","volume":"37","author":"A Abbasi","year":"2021","unstructured":"Abbasi A, Firouzi B, Sendur P (2021) On the application of Harris Hawks Optimization (HHO) algorithm to the design of microchannel heat sinks. Eng Comput 37:1409\u20131428. https:\/\/doi.org\/10.1007\/s00366-019-00892-0","journal-title":"Eng Comput"},{"key":"1487_CR63","doi-asserted-by":"publisher","first-page":"369","DOI":"10.1007\/s00366-019-00828-8","volume":"37","author":"H Moayedi","year":"2021","unstructured":"Moayedi H, Osouli A, Nguyen H, Rashid ASA (2021) A novel Harris hawks\u2019 Optimization and k-fold cross-validation predicting slope stability. Eng Comput 37:369\u2013379. https:\/\/doi.org\/10.1007\/s00366-019-00828-8","journal-title":"Eng Comput"},{"key":"1487_CR64","doi-asserted-by":"publisher","first-page":"175","DOI":"10.1016\/j.future.2020.04.008","volume":"111","author":"H Chen","year":"2020","unstructured":"Chen H, Heidari AA, Chen H, Wang M, Pan Z, Gandomi AH (2020) Multi-population differential evolution-assisted Harris hawks Optimization: framework and case studies. Futur Gener Comput Syst 111:175\u2013198. https:\/\/doi.org\/10.1016\/j.future.2020.04.008","journal-title":"Futur Gener Comput Syst"},{"key":"1487_CR65","doi-asserted-by":"publisher","DOI":"10.1080\/0305215X.2021.1919887","author":"B Firouzi","year":"2021","unstructured":"Firouzi B, Abbasi A, Sendur P (2021) Improvement of the computational efficiency of metaheuristic algorithms for Improvement of the computational efficiency of metaheuristic algorithms for the crack detection of cantilever beams using hybrid methods. Eng Optim. https:\/\/doi.org\/10.1080\/0305215X.2021.1919887","journal-title":"Eng Optim"},{"key":"1487_CR66","doi-asserted-by":"publisher","first-page":"76841","DOI":"10.1109\/ACCESS.2020.2982796","volume":"8","author":"Y Wei","year":"2020","unstructured":"Wei Y, Lv H, Chen M, Wang M, Heidari AA, Chen H, Li C (2020) Predicting entrepreneurial intention of students: an extreme learning machine with gaussian barebone Harris Hawks optimizer. IEEE Access 8:76841\u201376855. https:\/\/doi.org\/10.1109\/ACCESS.2020.2982796","journal-title":"IEEE Access"},{"key":"1487_CR67","doi-asserted-by":"publisher","first-page":"52","DOI":"10.1016\/j.apm.2020.03.024","volume":"84","author":"C Qu","year":"2020","unstructured":"Qu C, He W, Peng X, Peng X (2020) Harris Hawks optimization with information exchange. Appl Math Model 84:52\u201375. https:\/\/doi.org\/10.1016\/j.apm.2020.03.024","journal-title":"Appl Math Model"},{"key":"1487_CR68","doi-asserted-by":"publisher","first-page":"164887","DOI":"10.1109\/ACCESS.2019.2947308","volume":"7","author":"MR Elkadeem","year":"2019","unstructured":"Elkadeem MR, Abd Elaziz M, Ullah Z, Wang S, Sharshir SW (2019) Optimal planning of renewable energy-integrated distribution system considering uncertainties. IEEE Access. 7:164887\u2013164907. https:\/\/doi.org\/10.1109\/ACCESS.2019.2947308","journal-title":"IEEE Access."},{"key":"1487_CR69","doi-asserted-by":"publisher","first-page":"19","DOI":"10.5815\/ijisa.2013.05.03","volume":"5","author":"R Ebrahimzadeh","year":"2013","unstructured":"Ebrahimzadeh R, Jampour M (2013) Chaotic genetic algorithm based on lorenz chaotic system for optimization problems. Int J Intell Syst Appl 5:19\u201324. https:\/\/doi.org\/10.5815\/ijisa.2013.05.03","journal-title":"Int J Intell Syst Appl"},{"key":"1487_CR70","doi-asserted-by":"publisher","DOI":"10.1155\/2020\/6084917","author":"Y Ji","year":"2020","unstructured":"Ji Y, Tu J, Zhou H, Gui W, Liang G, Chen H, Wang M (2020) An adaptive chaotic sine cosine algorithm for constrained and unconstrained optimization. Complexity. https:\/\/doi.org\/10.1155\/2020\/6084917","journal-title":"Complexity"},{"key":"1487_CR71","doi-asserted-by":"publisher","DOI":"10.1109\/IranianCIS.2014.6802527","author":"H Afrabandpey","year":"2014","unstructured":"Afrabandpey H, Ghaffari M, Mirzaei A, Safayani M (2014) A novel Bat Algorithm based on chaos for optimization tasks, 2014 Iran. Conf Intell Syst ICIS. https:\/\/doi.org\/10.1109\/IranianCIS.2014.6802527","journal-title":"Conf Intell Syst ICIS"},{"key":"1487_CR72","doi-asserted-by":"publisher","first-page":"458","DOI":"10.1016\/j.jcde.2017.02.005","volume":"5","author":"M Kohli","year":"2018","unstructured":"Kohli M, Arora S (2018) Chaotic grey wolf optimization algorithm for constrained optimization problems. J Comput Des Eng 5:458\u2013472. https:\/\/doi.org\/10.1016\/j.jcde.2017.02.005","journal-title":"J Comput Des Eng"},{"key":"1487_CR73","doi-asserted-by":"publisher","first-page":"14555","DOI":"10.1016\/j.eswa.2011.05.027","volume":"38","author":"LY Chuang","year":"2011","unstructured":"Chuang LY, Hsiao CJ, Yang CH (2011) Chaotic particle swarm optimization for data clustering. Expert Syst Appl 38:14555\u201314563. https:\/\/doi.org\/10.1016\/j.eswa.2011.05.027","journal-title":"Expert Syst Appl"},{"key":"1487_CR74","doi-asserted-by":"publisher","first-page":"275","DOI":"10.1016\/j.jcde.2017.12.006","volume":"5","author":"G Kaur","year":"2018","unstructured":"Kaur G, Arora S (2018) Chaotic whale optimization algorithm. J Comput Des Eng 5:275\u2013284. https:\/\/doi.org\/10.1016\/j.jcde.2017.12.006","journal-title":"J Comput Des Eng"},{"key":"1487_CR75","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2019.103370","volume":"88","author":"AA Ewees","year":"2020","unstructured":"Ewees AA, Elaziz MA (2020) Performance analysis of Chaotic Multi-Verse Harris Hawks Optimization: a case study on solving engineering problems. Eng Appl Artif Intell 88:103370. https:\/\/doi.org\/10.1016\/j.engappai.2019.103370","journal-title":"Eng Appl Artif Intell"},{"key":"1487_CR76","doi-asserted-by":"publisher","DOI":"10.1007\/s00366-020-00994-0","volume-title":"A new hybrid chaotic atom search optimization based on tree-seed algorithm and Levy flight for solving optimization problems","author":"S Barshandeh","year":"2020","unstructured":"Barshandeh S, Haghzadeh M (2020) A new hybrid chaotic atom search optimization based on tree-seed algorithm and Levy flight for solving optimization problems. Springer, London. https:\/\/doi.org\/10.1007\/s00366-020-00994-0"},{"key":"1487_CR77","doi-asserted-by":"publisher","DOI":"10.1109\/ICCAKM46823.2020.9051509","author":"D Dhawale","year":"2020","unstructured":"Dhawale D, Kamboj VK (2020) HHHO-IGWO: A new hybrid harris hawks optimizer for solving global optimization problems. Proc Int Conf Comput Autom Knowl Manag. https:\/\/doi.org\/10.1109\/ICCAKM46823.2020.9051509","journal-title":"Proc Int Conf Comput Autom Knowl Manag"},{"key":"1487_CR78","doi-asserted-by":"publisher","first-page":"13086","DOI":"10.1109\/ACCESS.2020.2966582","volume":"8","author":"W Fu","year":"2020","unstructured":"Fu W, Shao K, Tan J, Wang K (2020) Fault diagnosis for rolling bearings based on composite multiscale fine-sorted dispersion entropy and SVM with hybrid mutation SCA-HHO algorithm optimization. IEEE Access 8:13086\u201313104. https:\/\/doi.org\/10.1109\/ACCESS.2020.2966582","journal-title":"IEEE Access"},{"key":"1487_CR79","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2019.106018","volume":"89","author":"VK Kamboj","year":"2020","unstructured":"Kamboj VK, Nandi A, Bhadoria A, Sehgal S (2020) An intensify Harris Hawks Optimizer for numerical and engineering optimization problems. Appl Soft Comput J 89:106018. https:\/\/doi.org\/10.1016\/j.asoc.2019.106018","journal-title":"Appl Soft Comput J"},{"key":"1487_CR80","doi-asserted-by":"publisher","DOI":"10.1016\/j.enconman.2020.112660","volume":"209","author":"HM Ridha","year":"2020","unstructured":"Ridha HM, Heidari AA, Wang M, Chen H (2020) Boosted mutation-based Harris Hawks Optimizer for parameters identification of single-diode solar cell models. Energy Convers Manag 209:112660. https:\/\/doi.org\/10.1016\/j.enconman.2020.112660","journal-title":"Energy Convers Manag"},{"key":"1487_CR81","doi-asserted-by":"publisher","first-page":"65891","DOI":"10.1109\/ACCESS.2020.2985596","volume":"8","author":"H Hu","year":"2020","unstructured":"Hu H, Ao Y, Bai Y, Cheng R, Xu T (2020) An improved Harris\u2019s Hawks Optimization for SAR target recognition and stock market index prediction. IEEE Access 8:65891\u201365910. https:\/\/doi.org\/10.1109\/ACCESS.2020.2985596","journal-title":"IEEE Access"},{"key":"1487_CR82","doi-asserted-by":"publisher","first-page":"52815","DOI":"10.1109\/ACCESS.2020.2980245","volume":"8","author":"A Selim","year":"2020","unstructured":"Selim A, Kamel S, Alghamdi AS, Jurado F (2020) Optimal placement of DGs in distribution system using an improved harris hawks optimizer based on single- and multi-objective approaches. IEEE Access 8:52815\u201352829. https:\/\/doi.org\/10.1109\/ACCESS.2020.2980245","journal-title":"IEEE Access"},{"key":"1487_CR83","doi-asserted-by":"publisher","DOI":"10.1016\/j.energy.2020.117804","volume":"203","author":"S Jiao","year":"2020","unstructured":"Jiao S, Chong G, Huang C, Hu H, Wang M, Heidari AA, Chen H, Zhao X (2020) Orthogonally adapted Harris Hawks Optimization for parameter estimation of photovoltaic models. Energy 203:117804. https:\/\/doi.org\/10.1016\/j.energy.2020.117804","journal-title":"Energy"},{"key":"1487_CR84","doi-asserted-by":"publisher","first-page":"1951","DOI":"10.1007\/s00158-020-02587-3","volume":"62","author":"C Zhong","year":"2020","unstructured":"Zhong C, Wang M, Dang C, Ke W, Guo S (2020) First-order reliability method based on Harris Hawks Optimization for high-dimensional reliability analysis. Struct Multidiscip Optim 62:1951\u20131968. https:\/\/doi.org\/10.1007\/s00158-020-02587-3","journal-title":"Struct Multidiscip Optim"},{"key":"1487_CR85","doi-asserted-by":"publisher","first-page":"14825","DOI":"10.1007\/s00500-020-04834-7","volume":"24","author":"Q Fan","year":"2020","unstructured":"Fan Q, Chen Z, Xia Z (2020) A novel quasi-reflected Harris hawks optimization algorithm for global optimization problems. Soft Comput 24:14825\u201314843. https:\/\/doi.org\/10.1007\/s00500-020-04834-7","journal-title":"Soft Comput"},{"key":"1487_CR86","doi-asserted-by":"publisher","first-page":"115020","DOI":"10.1016\/j.applthermaleng.2020.115020","volume":"170","author":"FA Essa","year":"2020","unstructured":"Essa FA, Abd Elaziz M, Elsheikh AH (2020) An enhanced productivity prediction model of active solar still using artificial neural network and Harris Hawks optimizer. Appl Therm Eng 170:115020. https:\/\/doi.org\/10.1016\/j.applthermaleng.2020.115020","journal-title":"Appl Therm Eng"},{"key":"1487_CR87","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/ACCESS.2019.2961811","volume":"8","author":"AS Menesy","year":"2020","unstructured":"Menesy AS, Sultan HM, Selim A, Ashmawy MG, Kamel S (2020) Developing and applying Chaotic Harris Hawks Optimization technique for extracting parameters of several proton exchange membrane fuel cell stacks. IEEE Access 8:1. https:\/\/doi.org\/10.1109\/ACCESS.2019.2961811","journal-title":"IEEE Access"},{"key":"1487_CR88","doi-asserted-by":"crossref","unstructured":"Yin Q, Cao B, Li X, Wang, B, Zhang, Q, Wei X (2020) An intelligent optimization algorithm for constructing a DNA storage code: NOL-HHO. Int J Mol Sci 21(6):2191","DOI":"10.3390\/ijms21062191"},{"key":"1487_CR89","doi-asserted-by":"publisher","first-page":"69579","DOI":"10.1109\/ACCESS.2020.2987078","volume":"8","author":"C Li","year":"2020","unstructured":"Li C, Li J, Chen H (2020) A meta-heuristic-based approach for Qos-aware service composition. IEEE Access 8:69579\u201369592. https:\/\/doi.org\/10.1109\/ACCESS.2020.2987078","journal-title":"IEEE Access"},{"key":"1487_CR90","doi-asserted-by":"publisher","first-page":"5882","DOI":"10.1016\/j.jmrt.2019.09.060","volume":"8","author":"TA Shehabeldeen","year":"2019","unstructured":"Shehabeldeen TA, Elaziz MA, Elsheikh AH, Zhou J (2019) Modeling of friction stir welding process using adaptive neuro-fuzzy inference system integrated with Harris Hawks Optimizer. J Mater Res Technol 8:5882\u20135892. https:\/\/doi.org\/10.1016\/j.jmrt.2019.09.060","journal-title":"J Mater Res Technol"},{"key":"1487_CR91","doi-asserted-by":"publisher","first-page":"184468","DOI":"10.1109\/ACCESS.2019.2958279","volume":"7","author":"S Birogul","year":"2019","unstructured":"Birogul S (2019) Hybrid harris hawk optimization based on differential evolution (HHODE) algorithm for optimal power flow problem. IEEE Access 7:184468\u2013184488. https:\/\/doi.org\/10.1109\/ACCESS.2019.2958279","journal-title":"IEEE Access"},{"key":"1487_CR92","doi-asserted-by":"publisher","first-page":"437","DOI":"10.1007\/s00366-019-00834-w","volume":"37","author":"H Moayedi","year":"2021","unstructured":"Moayedi H, Abdullahi MM, Nguyen H, Rashid ASA (2021) Comparison of dragonfly algorithm and Harris hawks optimization evolutionary data mining techniques for the assessment of bearing capacity of footings over two-layer foundation soils. Eng Comput 37:437\u2013447. https:\/\/doi.org\/10.1007\/s00366-019-00834-w","journal-title":"Eng Comput"},{"key":"1487_CR93","doi-asserted-by":"publisher","first-page":"447","DOI":"10.1016\/j.jcde.2018.08.001","volume":"6","author":"H Rezaie","year":"2019","unstructured":"Rezaie H, Kazemi-Rahbar MH, Vahidi B, Rastegar H (2019) Solution of combined economic and emission dispatch problem using a novel chaotic improved harmony search algorithm. J Comput Des Eng 6:447\u2013467. https:\/\/doi.org\/10.1016\/j.jcde.2018.08.001","journal-title":"J Comput Des Eng"},{"key":"1487_CR94","doi-asserted-by":"publisher","DOI":"10.1155\/2018\/4945157","author":"A Saxena","year":"2018","unstructured":"Saxena A, Shekhawat S, Kumar R (2018) Application and development of enhanced chaotic grasshopper optimization algorithms. Model Simul Eng. https:\/\/doi.org\/10.1155\/2018\/4945157","journal-title":"Model Simul Eng"},{"key":"1487_CR95","doi-asserted-by":"publisher","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 (2020) Parameters identification of photovoltaic cells and modules using diversification-enriched Harris hawks optimization with chaotic drifts. J Clean Prod 244:118778. https:\/\/doi.org\/10.1016\/j.jclepro.2019.118778","journal-title":"J Clean Prod"},{"key":"1487_CR96","doi-asserted-by":"publisher","DOI":"10.1109\/EITCE47263.2019.9095091","author":"ZM Gao","year":"2019","unstructured":"Gao ZM, Zhao J, Hu YR, Chen HF (2019) The improved harris hawk optimization algorithm with the tent map. IEEE Int Conf Electron Inf Technol Comput Eng. https:\/\/doi.org\/10.1109\/EITCE47263.2019.9095091","journal-title":"IEEE Int Conf Electron Inf Technol Comput Eng"},{"key":"1487_CR97","doi-asserted-by":"publisher","first-page":"1525","DOI":"10.1126\/science.239.4847.1525","volume":"239","author":"JC Bednarz","year":"1988","unstructured":"Bednarz JC (1988) Cooperative hunting in Harris\u2019 Hawks (Parabuteo unicinctus). Science (80-) 239:1525\u20131527. https:\/\/doi.org\/10.1126\/science.239.4847.1525","journal-title":"Science (80-)"},{"key":"1487_CR98","doi-asserted-by":"publisher","first-page":"1437","DOI":"10.1016\/j.pnsc.2008.03.029","volume":"18","author":"J Wang","year":"2008","unstructured":"Wang J, Wang D (2008) Particle swarm optimization with a leader and followers. Prog Nat Sci 18:1437\u20131443. https:\/\/doi.org\/10.1016\/j.pnsc.2008.03.029","journal-title":"Prog Nat Sci"},{"key":"1487_CR99","first-page":"829","volume":"26","author":"J Xie","year":"2013","unstructured":"Xie J, Zhou YQ, Chen H (2013) A bat algorithm based on L\u00e9vy flights trajectory, Moshi Shibie Yu Rengong Zhineng\/Pattern Recognit. Artif Intell 26:829\u2013837","journal-title":"Artif Intell"},{"key":"1487_CR100","doi-asserted-by":"publisher","first-page":"221","DOI":"10.1002\/9780470640425.ch17","volume-title":"Engineering optimization: an introduction with metaheuristic applications","author":"XS Yang","year":"2010","unstructured":"Yang XS (2010) Firefly algorithm. In: Ch M (ed) Engineering optimization: an introduction with metaheuristic applications. John Wiley and Sons Inc, Hoboken, p 221"},{"key":"1487_CR101","doi-asserted-by":"publisher","first-page":"83","DOI":"10.1109\/59.485989","volume":"11","author":"SA Kazarlis","year":"1996","unstructured":"Kazarlis SA (1996) A genetic algorithm solution to the unit commitment problem. IEEE Trans Power Syst 11:83\u201392","journal-title":"IEEE Trans Power Syst"},{"key":"1487_CR102","doi-asserted-by":"publisher","first-page":"256","DOI":"10.1007\/s10489-013-0458-0","volume":"40","author":"E Cuevas","year":"2014","unstructured":"Cuevas E, Echavarr\u00eda A, Ram\u00edrez-Orteg\u00f3n MA (2014) An optimization algorithm inspired by the States of Matter that improves the balance between exploration and exploitation. Appl Intell 40:256\u2013272. https:\/\/doi.org\/10.1007\/s10489-013-0458-0","journal-title":"Appl Intell"},{"key":"1487_CR103","doi-asserted-by":"crossref","unstructured":"Yang XS, Karamanoglu M, He X (2014) Flower pollination algorithm: a novel approach for multiobjective optimization. Eng Optim 46(9):1222\u20131237","DOI":"10.1080\/0305215X.2013.832237"},{"key":"1487_CR104","doi-asserted-by":"crossref","unstructured":"Jagodzi\u0144ski D, Arabas J (2017) A differential evolution strategy. In 2017 IEEE Congress on Evolutionary Computation\n(CEC), pp 1872\u20131876","DOI":"10.1109\/CEC.2017.7969529"},{"key":"1487_CR105","doi-asserted-by":"publisher","first-page":"80","DOI":"10.1016\/j.advengsoft.2015.01.010","volume":"83","author":"S Mirjalili","year":"2015","unstructured":"Mirjalili S (2015) The ant lion optimizer. Adv Eng Softw 83:80\u201398. https:\/\/doi.org\/10.1016\/j.advengsoft.2015.01.010","journal-title":"Adv Eng Softw"},{"key":"1487_CR106","doi-asserted-by":"publisher","DOI":"10.1007\/s00366-021-01409-4","author":"D Dhawale","year":"2021","unstructured":"Dhawale D, Kamboj VK, Anand P (2021) An effective solution to numerical and multi-disciplinary design optimization problems using chaotic slime mold algorithm, Springer. London. https:\/\/doi.org\/10.1007\/s00366-021-01409-4","journal-title":"London"},{"key":"1487_CR107","doi-asserted-by":"publisher","first-page":"1053","DOI":"10.1007\/s00521-015-1920-1","volume":"27","author":"S Mirjalili","year":"2016","unstructured":"Mirjalili S (2016) Dragonfly algorithm: a new meta-heuristic optimization technique for solving single-objective, discrete, and multi-objective problems. Neural Comput Appl 27:1053\u20131073. https:\/\/doi.org\/10.1007\/s00521-015-1920-1","journal-title":"Neural Comput Appl"},{"key":"1487_CR108","first-page":"21","volume":"6","author":"H Nezamabadi-pour","year":"2008","unstructured":"Nezamabadi-pour H, Rostami-sharbabaki M, Maghfoori-Farsangi M (2008) Binary particle swarm optimization: challenges and new solutions. J Comput Soc Iran 6:21\u201332","journal-title":"J Comput Soc Iran"},{"key":"1487_CR109","doi-asserted-by":"publisher","first-page":"2232","DOI":"10.1016\/j.ins.2009.03.004","volume":"179","author":"E Rashedi","year":"2009","unstructured":"Rashedi E, Nezamabadi-Pour H, Saryazdi S (2009) GSA: a gravitational search algorithm. Inf Sci 179:2232","journal-title":"Inf Sci"},{"key":"1487_CR110","volume-title":"Holland, adaptation in natural and artificial systems","author":"H John","year":"1992","unstructured":"John H (1992) Holland, adaptation in natural and artificial systems. MIT Press, Cambridge"},{"key":"1487_CR111","doi-asserted-by":"publisher","DOI":"10.1109\/SIBGRAPI.2012.47","author":"RYM Nakamura","year":"2012","unstructured":"Nakamura RYM, Pereira LAM, Costa KA, Rodrigues D, Papa JP, Yang XS (2012) BBA: A binary bat algorithm for feature selection Brazilian Symp. Comput Graph Image Process. https:\/\/doi.org\/10.1109\/SIBGRAPI.2012.47","journal-title":"Comput Graph Image Process"},{"key":"1487_CR112","doi-asserted-by":"publisher","first-page":"341","DOI":"10.1023\/A:1008202821328","volume":"11","author":"R Storn","year":"1997","unstructured":"Storn R, Price K (1997) Differential evolution: a simple and efficient heuristic for global optimization over continuous spaces. J Glob Optim 11:341\u2013359. https:\/\/doi.org\/10.1023\/A:1008202821328","journal-title":"J Glob Optim"},{"key":"1487_CR113","doi-asserted-by":"publisher","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 29:17\u201335. https:\/\/doi.org\/10.1007\/s00366-011-0241-y","journal-title":"Eng Comput"},{"key":"1487_CR114","doi-asserted-by":"publisher","first-page":"735","DOI":"10.1080\/03052150108940941","volume":"33","author":"T Ray","year":"2001","unstructured":"Ray T, Saini P (2001) Engineering design optimization using a swarm with an intelligent information sharing among individuals. Eng Optim 33:735\u2013748. https:\/\/doi.org\/10.1080\/03052150108940941","journal-title":"Eng Optim"},{"key":"1487_CR115","doi-asserted-by":"publisher","first-page":"399","DOI":"10.1080\/03052150500066737","volume":"37","author":"JFA Tsai","year":"2005","unstructured":"Tsai JFA (2005) Global optimization of nonlinear fractional programming problems in engineering design. Eng Optim 37:399\u2013409. https:\/\/doi.org\/10.1080\/03052150500066737","journal-title":"Eng Optim"},{"key":"1487_CR116","doi-asserted-by":"publisher","first-page":"2592","DOI":"10.1016\/j.asoc.2012.11.026","volume":"13","author":"A Sadollah","year":"2013","unstructured":"Sadollah A, Bahreininejad A, Eskandar H, Hamdi M (2013) Mine blast algorithm: a new population based algorithm for solving constrained engineering optimization problems. Appl Soft Comput J 13:2592\u20132612. https:\/\/doi.org\/10.1016\/j.asoc.2012.11.026","journal-title":"Appl Soft Comput J"},{"key":"1487_CR117","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2019.103300","volume":"87","author":"W Zhao","year":"2020","unstructured":"Zhao W, Zhang Z, Wang L (2020) Manta ray foraging optimization: an effective bio-inspired optimizer for engineering applications. Eng Appl Artif Intell 87:103300. https:\/\/doi.org\/10.1016\/j.engappai.2019.103300","journal-title":"Eng Appl Artif Intell"},{"key":"1487_CR118","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-85984-0_20","author":"B Niu","year":"2008","unstructured":"Niu B, Li L (2008) A novel PSO-DE-Based hybrid algorithm for global optimization. Lect Notes Comput Sci. https:\/\/doi.org\/10.1007\/978-3-540-85984-0_20","journal-title":"Lect Notes Comput Sci"},{"key":"1487_CR119","doi-asserted-by":"publisher","DOI":"10.1109\/SSCI.2016.7849998","author":"IA Hameed","year":"2016","unstructured":"Hameed IA, Bye RT, Osen OL (2016) Grey wolf optimizer (GWO) for automated offshore crane design. IEEE Symp Ser Comput Intell. https:\/\/doi.org\/10.1109\/SSCI.2016.7849998","journal-title":"IEEE Symp Ser Comput Intell"},{"key":"1487_CR120","unstructured":"Deb K, Goyal M (1996) A combined genetic adaptive search (GeneAS) for engineering design. Comput Sci Inf 26:30\u201345"},{"key":"1487_CR121","doi-asserted-by":"publisher","first-page":"398","DOI":"10.1109\/TEVC.2008.927706","volume":"13","author":"AK Qin","year":"2009","unstructured":"Qin AK, Huang VL, Suganthan PN (2009) Differential evolution algorithm with strategy adaptation for global numerical optimization. IEEE Trans Evol Comput 13:398\u2013417. https:\/\/doi.org\/10.1109\/TEVC.2008.927706","journal-title":"IEEE Trans Evol Comput"},{"key":"1487_CR122","doi-asserted-by":"publisher","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":"2002","unstructured":"Chickermane H, Gea HC (2002) Structural optimization using a new local approximation method. Int J Numer Methods Eng 39:829\u2013846. https:\/\/doi.org\/10.1002\/(sici)1097-0207(19960315)39:5%3c829::aid-nme884%3e3.0.co;2-u","journal-title":"Int J Numer Methods Eng"},{"key":"1487_CR123","doi-asserted-by":"publisher","first-page":"89","DOI":"10.1016\/j.engappai.2006.03.003","volume":"20","author":"Q He","year":"2007","unstructured":"He Q, Wang L (2007) An effective co-evolutionary particle swarm optimization for constrained engineering design problems. Eng Appl Artif Intell 20:89\u201399. https:\/\/doi.org\/10.1016\/j.engappai.2006.03.003","journal-title":"Eng Appl Artif Intell"},{"key":"1487_CR124","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/TEVC.2004.836819","volume":"9","author":"E Mezura-Montes","year":"2005","unstructured":"Mezura-Montes E, Coello Coello CA (2005) A simple multimembered evolution strategy to solve constrained optimization problems, IEEE Trans. Evol Comput 9:1\u201317. https:\/\/doi.org\/10.1109\/TEVC.2004.836819","journal-title":"Evol Comput"},{"key":"1487_CR125","doi-asserted-by":"publisher","DOI":"10.2514\/6.1990-1179","author":"K Deb","year":"1990","unstructured":"Deb K (1990) Optimal design of a class of welded structures via genetic algorithms. Collect Tech Pap AIAA\/ASME\/ASCE\/AHS\/ASC Struct Dyn Mater Conf. https:\/\/doi.org\/10.2514\/6.1990-1179","journal-title":"Collect Tech Pap AIAA\/ASME\/ASCE\/AHS\/ASC Struct Dyn Mater Conf"},{"key":"1487_CR126","doi-asserted-by":"publisher","first-page":"1567","DOI":"10.1016\/j.amc.2006.11.033","volume":"188","author":"M Mahdavi","year":"2007","unstructured":"Mahdavi M, Fesanghary M, Damangir E (2007) An improved harmony search algorithm for solving optimization problems. Appl Math Comput 188:1567\u20131579. https:\/\/doi.org\/10.1016\/j.amc.2006.11.033","journal-title":"Appl Math Comput"},{"key":"1487_CR127","doi-asserted-by":"publisher","first-page":"774","DOI":"10.1016\/j.asoc.2015.09.007","volume":"37","author":"G Wu","year":"2015","unstructured":"Wu G, Pedrycz W, Suganthan PN, Mallipeddi R (2015) A variable reduction strategy for evolutionary algorithms handling equality constraints. Appl Soft Comput J 37:774\u2013786. https:\/\/doi.org\/10.1016\/j.asoc.2015.09.007","journal-title":"Appl Soft Comput J"},{"key":"1487_CR128","doi-asserted-by":"publisher","first-page":"58","DOI":"10.1016\/j.asoc.2015.01.050","volume":"30","author":"A Sadollah","year":"2015","unstructured":"Sadollah A, Eskandar H, Bahreininejad A, Kim JH (2015) Water cycle algorithm with evaporation rate for solving constrained and unconstrained optimization problems. Appl Soft Comput J 30:58\u201371. https:\/\/doi.org\/10.1016\/j.asoc.2015.01.050","journal-title":"Appl Soft Comput J"},{"key":"1487_CR129","doi-asserted-by":"publisher","first-page":"217","DOI":"10.1007\/s41403-018-0051-2","volume":"3","author":"VK Kamboj","year":"2018","unstructured":"Kamboj VK, Bhadoria A, Gupta N (2018) A novel hybrid GWO-PS algorithm for standard benchmark optimization problems. Ina Lett 3:217\u2013241. https:\/\/doi.org\/10.1007\/s41403-018-0051-2","journal-title":"Ina Lett"},{"key":"1487_CR130","doi-asserted-by":"publisher","first-page":"781","DOI":"10.1016\/j.compstruc.2004.01.002","volume":"82","author":"KS Lee","year":"2004","unstructured":"Lee KS, Geem ZW (2004) A new structural optimization method based on the harmony search algorithm. Comput Struct 82:781\u2013798. https:\/\/doi.org\/10.1016\/j.compstruc.2004.01.002","journal-title":"Comput Struct"},{"key":"1487_CR131","doi-asserted-by":"publisher","first-page":"1021","DOI":"10.1115\/1.3438995","volume":"98","author":"KM Ragsdell","year":"1976","unstructured":"Ragsdell KM, Phillips DT (1976) Optimal design of a class of welded structures using geometric programming. J Manuf Sci Eng Trans ASME 98:1021\u20131025. https:\/\/doi.org\/10.1115\/1.3438995","journal-title":"J Manuf Sci Eng Trans ASME"},{"key":"1487_CR132","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 DP (2011) Teaching-learning-based optimization: A novel method for constrained mechanical design optimization problems. CAD Comput Aided Des 43:303\u2013315. https:\/\/doi.org\/10.1016\/j.cad.2010.12.015","journal-title":"CAD Comput Aided Des"},{"key":"1487_CR133","doi-asserted-by":"publisher","first-page":"3951","DOI":"10.1016\/j.apm.2015.10.040","volume":"40","author":"P Savsani","year":"2016","unstructured":"Savsani P, Savsani V (2016) Passing vehicle search (PVS): a novel metaheuristic algorithm. Appl Math Model 40:3951\u20133978. https:\/\/doi.org\/10.1016\/j.apm.2015.10.040","journal-title":"Appl Math Model"}],"container-title":["Engineering with Computers"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00366-021-01487-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00366-021-01487-4\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00366-021-01487-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,4,28]],"date-time":"2023-04-28T21:04:39Z","timestamp":1682715879000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00366-021-01487-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,9,21]]},"references-count":133,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2023,4]]}},"alternative-id":["1487"],"URL":"https:\/\/doi.org\/10.1007\/s00366-021-01487-4","relation":{},"ISSN":["0177-0667","1435-5663"],"issn-type":[{"value":"0177-0667","type":"print"},{"value":"1435-5663","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,9,21]]},"assertion":[{"value":"10 March 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 July 2021","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 September 2021","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}