{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,27]],"date-time":"2026-06-27T19:38:38Z","timestamp":1782589118425,"version":"3.54.5"},"reference-count":69,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2021,5,28]],"date-time":"2021-05-28T00:00:00Z","timestamp":1622160000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2021,5,28]],"date-time":"2021-05-28T00:00:00Z","timestamp":1622160000000},"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":["J Ambient Intell Human Comput"],"published-print":{"date-parts":[[2023,1]]},"DOI":"10.1007\/s12652-021-03304-8","type":"journal-article","created":{"date-parts":[[2021,5,28]],"date-time":"2021-05-28T14:15:28Z","timestamp":1622211328000},"page":"431-467","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":71,"title":["A hybrid whale optimization algorithm for global optimization"],"prefix":"10.1007","volume":"14","author":[{"given":"Sanjoy","family":"Chakraborty","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3475-018X","authenticated-orcid":false,"given":"Apu Kumar","family":"Saha","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sushmita","family":"Sharma","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ratul","family":"Chakraborty","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sudhan","family":"Debnath","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2021,5,28]]},"reference":[{"issue":"4","key":"3304_CR1","doi-asserted-by":"publisher","first-page":"723","DOI":"10.1007\/s11036-018-1005-3","volume":"23","author":"M Abdel-Basset","year":"2018","unstructured":"Abdel-Basset M, El-Shahat D, El-henawy I, Sangaiah AK, Ahmed SH (2018a) A novel whale optimization algorithm for cryptanalysis in MerklE\u2212Hellman cryptosystem. Mobile Netw Appl 23(4):723\u2013733. https:\/\/doi.org\/10.1007\/s11036-018-1005-3","journal-title":"Mobile Netw Appl"},{"key":"3304_CR2","doi-asserted-by":"publisher","first-page":"129","DOI":"10.1016\/j.future.2018.03.020","volume":"85","author":"M Abdel-Basset","year":"2018","unstructured":"Abdel-Basset M, Manogaran G, El-Shahat D, Mirjalili S (2018b) A hybrid whale optimization algorithm based on local search strategy for the permutation flow shop scheduling problem. Futur Gener Comput Syst 85:129\u2013145. https:\/\/doi.org\/10.1016\/j.future.2018.03.020","journal-title":"Futur Gener Comput Syst"},{"issue":"2","key":"3304_CR3","doi-asserted-by":"publisher","first-page":"547","DOI":"10.1007\/s00521-019-04170-4","volume":"32","author":"M Abdullahi","year":"2020","unstructured":"Abdullahi M, Ngadi MA, Dishing SI, Abdulhamid SM, Usman MJ (2020) A survey of symbiotic organisms search algorithms and applications. Neural Comput Appl 32(2):547\u2013566. https:\/\/doi.org\/10.1007\/s00521-019-04170-4","journal-title":"Neural Comput Appl"},{"key":"3304_CR4","doi-asserted-by":"publisher","first-page":"7461","DOI":"10.1166\/asl.2018.12959","volume":"24","author":"H Alamri","year":"2018","unstructured":"Alamri H, Alsariera Y, Zamli K (2018) Opposition-based whale optimization algorithm. Adv Sci Lett 24:7461\u20137464. https:\/\/doi.org\/10.1166\/asl.2018.12959","journal-title":"Adv Sci Lett"},{"key":"3304_CR5","doi-asserted-by":"publisher","unstructured":"Anandita S, Rosmansyah Y, Dabarsyah B, Choi JU (2015) Implementation of dendritic cell algorithm as an anomaly detection method for port scanning attack. In: 2015 international conference on information technology systems and innovation (ICITSI). https:\/\/doi.org\/https:\/\/doi.org\/10.1109\/icitsi.2015.7437688","DOI":"10.1109\/icitsi.2015.7437688"},{"issue":"1","key":"3304_CR6","doi-asserted-by":"publisher","first-page":"69","DOI":"10.1016\/0303-2647(94)90062-0","volume":"33","author":"PJ Angeline","year":"1994","unstructured":"Angeline PJ (1994) Genetic programming: on the programming of computers by means of natural selection. Biosystems 33(1):69\u201373. https:\/\/doi.org\/10.1016\/0303-2647(94)90062-0","journal-title":"Biosystems"},{"issue":"3","key":"3304_CR7","doi-asserted-by":"publisher","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(3):715\u2013734. https:\/\/doi.org\/10.1007\/s00500-018-3102-4","journal-title":"Soft Comput"},{"key":"3304_CR8","doi-asserted-by":"publisher","first-page":"215","DOI":"10.1016\/j.ins.2016.10.039","volume":"378","author":"NH Awad","year":"2017","unstructured":"Awad NH, Ali MZ, Suganthan PN, Reynolds RG (2017) CADE: a hybridization of cultural algorithm and differential evolution for numerical optimization. Inf Sci 378:215\u2013241. https:\/\/doi.org\/10.1016\/j.ins.2016.10.039","journal-title":"Inf Sci"},{"key":"3304_CR9","doi-asserted-by":"publisher","first-page":"107086","DOI":"10.1016\/j.cie.2020.107086","volume":"153","author":"S Chakraborty","year":"2020","unstructured":"Chakraborty S, Saha AK, Sharma S, Mirjalili S, Chakraborty R (2020) A novel enhanced whale optimization algorithm for global optimization. Comput Ind Eng 153:107086. https:\/\/doi.org\/10.1016\/j.cie.2020.107086","journal-title":"Comput Ind Eng"},{"key":"3304_CR10","doi-asserted-by":"publisher","first-page":"45","DOI":"10.1016\/j.apm.2019.02.004","volume":"71","author":"H Chen","year":"2019","unstructured":"Chen H, Xu Y, Wang M, Zhao X (2019) A balanced whale optimization algorithm for constrained engineering design problems. Appl Math Model 71:45\u201359. https:\/\/doi.org\/10.1016\/j.apm.2019.02.004","journal-title":"Appl Math Model"},{"key":"3304_CR11","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"},{"issue":"11\u201312","key":"3304_CR12","doi-asserted-by":"publisher","first-page":"1245","DOI":"10.1016\/S0045-7825(01)00323-1","volume":"191","author":"CA Coello Coello","year":"2002","unstructured":"Coello Coello CA (2002) Theoretical and numerical constraint-handling techniques used with evolutionary algorithms: a survey of the state of the art. Comput Methods Appl Mech Eng 191(11\u201312):1245\u20131287. https:\/\/doi.org\/10.1016\/S0045-7825(01)00323-1","journal-title":"Comput Methods Appl Mech Eng"},{"key":"3304_CR13","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.swevo.2016.01.004","volume":"27","author":"S Das","year":"2016","unstructured":"Das S, Mullick SS, Suganthan PN (2016) Recent advances in differential evolution\u2014an updated survey. Swarm Evol Comput 27:1\u201330. https:\/\/doi.org\/10.1016\/j.swevo.2016.01.004","journal-title":"Swarm Evol Comput"},{"key":"3304_CR14","doi-asserted-by":"publisher","first-page":"683","DOI":"10.1016\/j.asoc.2017.08.002","volume":"61","author":"DTT Do","year":"2017","unstructured":"Do DTT, Lee J (2017) A modified symbiotic organisms search (mSOS) algorithm for optimization of pin-jointed structures. Appl Soft Comput J 61:683\u2013699. https:\/\/doi.org\/10.1016\/j.asoc.2017.08.002","journal-title":"Appl Soft Comput J"},{"key":"3304_CR15","doi-asserted-by":"publisher","first-page":"17","DOI":"10.1016\/j.jocs.2018.12.005","volume":"31","author":"MA Elhosseini","year":"2019","unstructured":"Elhosseini MA, Haikal AY, Badawy M, Khashan N (2019) Biped robot stability based on an A-C parametric Whale Optimization Algorithm. J Comput Sci 31:17\u201332. https:\/\/doi.org\/10.1016\/j.jocs.2018.12.005","journal-title":"J Comput Sci"},{"key":"3304_CR16","doi-asserted-by":"publisher","first-page":"184","DOI":"10.1016\/j.eswa.2018.10.045","volume":"119","author":"AE Ezugwu","year":"2019","unstructured":"Ezugwu AE, Prayogo D (2019) Symbiotic organisms search algorithm: theory, recent advances and applications. Expert Syst Appl 119:184\u2013209. https:\/\/doi.org\/10.1016\/j.eswa.2018.10.045","journal-title":"Expert Syst Appl"},{"key":"3304_CR17","doi-asserted-by":"publisher","unstructured":"Fan Q, Chen Z, Zhang W, Fang X (2020) ESSAWOA: Enhanced Whale Optimization Algorithm integrated with Salp Swarm Algorithm for global optimization. Eng Comput 0123456789. https:\/\/doi.org\/https:\/\/doi.org\/10.1007\/s00366-020-01189-3","DOI":"10.1007\/s00366-020-01189-3"},{"key":"3304_CR18","doi-asserted-by":"publisher","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. https:\/\/doi.org\/10.1016\/j.knosys.2019.105190","journal-title":"Knowl-Based Syst"},{"issue":"2","key":"3304_CR19","doi-asserted-by":"publisher","first-page":"439","DOI":"10.1007\/s12667-017-0232-1","volume":"9","author":"D Guha","year":"2018","unstructured":"Guha D, Roy PK, Banerjee S (2018) Symbiotic organism search algorithm applied to load frequency control of multi-area power system. Energy Syst 9(2):439\u2013468. https:\/\/doi.org\/10.1007\/s12667-017-0232-1","journal-title":"Energy Syst"},{"key":"3304_CR20","doi-asserted-by":"publisher","unstructured":"Gupta S, Saurabh K (2017) Modified artificial killer whale optimization algorithm for maximum power point tracking under partial shading condition. In: Proceedings\u20142017 international conference on recent trends in electrical, electronics and computing technologies, ICRTEECT 2017, 87\u201392. https:\/\/doi.org\/https:\/\/doi.org\/10.1109\/ICRTEECT.2017.34","DOI":"10.1109\/ICRTEECT.2017.34"},{"key":"3304_CR21","doi-asserted-by":"publisher","unstructured":"Iakubovskii DV, Krupenev DS, Boyarkin DA (2019) Application the differential evolution for solving the problem of minimizing the power shortage of electric power systems. E3S Web of Conferences, 114, 03002 https:\/\/doi.org\/https:\/\/doi.org\/10.1051\/e3sconf\/201911403002","DOI":"10.1051\/e3sconf\/201911403002"},{"issue":"3","key":"3304_CR22","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 Design Eng 5(3):275\u2013284. https:\/\/doi.org\/10.1016\/j.jcde.2017.12.006","journal-title":"J Comput Design Eng"},{"issue":"1","key":"3304_CR23","doi-asserted-by":"publisher","first-page":"23","DOI":"10.1007\/s00158-015-1396-8","volume":"54","author":"A Kaveh","year":"2016","unstructured":"Kaveh A, Bakhshpoori T (2016) A new metaheuristic for continuous structural optimization: water evaporation optimization. Struct Multidiscip Optim 54(1):23\u201343. https:\/\/doi.org\/10.1007\/s00158-015-1396-8","journal-title":"Struct Multidiscip Optim"},{"issue":"3","key":"3304_CR24","doi-asserted-by":"publisher","first-page":"345","DOI":"10.1080\/15397734.2016.1213639","volume":"45","author":"A Kaveh","year":"2017","unstructured":"Kaveh A, Ghazaan MI (2017) Enhanced whale optimization algorithm for sizing optimization of skeletal structures. Mech Based Des Struct Mach 45(3):345\u2013362. https:\/\/doi.org\/10.1080\/15397734.2016.1213639","journal-title":"Mech Based Des Struct Mach"},{"key":"3304_CR25","doi-asserted-by":"publisher","unstructured":"Kennedy, J., Eberhart, R. (1995). Particle swarm optimization. In: Proceedings of ICNN\u201995\u2014international conference on neural networks, 4, 1942\u20131948. https:\/\/doi.org\/https:\/\/doi.org\/10.1109\/ICNN.1995.488968","DOI":"10.1109\/ICNN.1995.488968"},{"issue":"12","key":"3304_CR26","doi-asserted-by":"publisher","first-page":"9121","DOI":"10.1007\/s00500-019-04443-z","volume":"24","author":"A Khatri","year":"2020","unstructured":"Khatri A, Gaba A, Rana KPS, Kumar V (2020) A novel life choicE\u2212based optimizer. Soft Comput 24(12):9121\u20139141. https:\/\/doi.org\/10.1007\/s00500-019-04443-z","journal-title":"Soft Comput"},{"issue":"7","key":"3304_CR27","doi-asserted-by":"publisher","first-page":"2095","DOI":"10.1007\/s00521-018-3796-3","volume":"32","author":"V Kumar","year":"2020","unstructured":"Kumar V, Kumar D (2020) Binary whale optimization algorithm and its application to unit commitment problem. Neural Comput Appl 32(7):2095\u20132123. https:\/\/doi.org\/10.1007\/s00521-018-3796-3","journal-title":"Neural Comput Appl"},{"key":"3304_CR28","doi-asserted-by":"publisher","first-page":"41","DOI":"10.1016\/j.future.2017.10.047","volume":"81","author":"J Kumar","year":"2018","unstructured":"Kumar J, Singh AK (2018) Workload prediction in cloud using artificial neural network and adaptive differential evolution. Futur Gener Comput Syst 81:41\u201352. https:\/\/doi.org\/10.1016\/j.future.2017.10.047","journal-title":"Futur Gener Comput Syst"},{"issue":"4","key":"3304_CR29","doi-asserted-by":"publisher","first-page":"1269","DOI":"10.1007\/s00366-018-0662-y","volume":"35","author":"S Kumar","year":"2019","unstructured":"Kumar S, Tejani GG, Mirjalili S (2019) Modified symbiotic organisms search for structural optimization. Eng Comput 35(4):1269\u20131296. https:\/\/doi.org\/10.1007\/s00366-018-0662-y","journal-title":"Eng Comput"},{"key":"3304_CR30","doi-asserted-by":"publisher","unstructured":"Kumar, A., Wu, G., Ali, M. Z., Mallipeddi, R., Suganthan, P. N., & Das, S. (2020). A test-suite of non-convex constrained optimization problems from the real-world and some baseline results. Swarm and Evolutionary Computation, 56. https:\/\/doi.org\/https:\/\/doi.org\/10.1016\/j.swevo.2020.100693","DOI":"10.1016\/j.swevo.2020.100693"},{"key":"3304_CR31","unstructured":"Lampinen, J., Zelinka, I. (2000). On stagnation of the differential evolution algorithm. In: O\u02c6smera P(ed) Proceedings of 6th international mendel conference on soft computing, 76\u201383."},{"key":"3304_CR32","doi-asserted-by":"publisher","unstructured":"Li G, Lin Q, Cui L, Du Z, Liang Z, Chen J, Lu N, Ming Z (2016) A novel hybrid differential evolution algorithm with modified CoDE and JADE. Appl Soft Comput 47. https:\/\/doi.org\/https:\/\/doi.org\/10.1016\/j.asoc .2016.06 .011","DOI":"10.1016\/j.asoc"},{"key":"3304_CR33","doi-asserted-by":"publisher","first-page":"6168","DOI":"10.1109\/ACCESS.2017.2695498","volume":"5","author":"Y Ling","year":"2017","unstructured":"Ling Y, Zhou Y, Luo Q (2017) L\u00e9vy flight trajectory-based whale optimization algorithm for global optimization. IEEE Access 5:6168\u20136186. https:\/\/doi.org\/10.1109\/ACCESS.2017.2695498","journal-title":"IEEE Access"},{"issue":"5","key":"3304_CR34","doi-asserted-by":"publisher","first-page":"1982","DOI":"10.1007\/s10489-018-1362-4","volume":"49","author":"J Luo","year":"2019","unstructured":"Luo J, Shi B (2019) A hybrid whale optimization algorithm based on modified differential evolution for global optimization problems. Appl Intell 49(5):1982\u20132000. https:\/\/doi.org\/10.1007\/s10489-018-1362-4","journal-title":"Appl Intell"},{"key":"3304_CR35","doi-asserted-by":"publisher","first-page":"441","DOI":"10.1016\/j.asoc.2017.11.006","volume":"62","author":"M Mafarja","year":"2018","unstructured":"Mafarja M, Mirjalili S (2018) Whale optimization approaches for wrapper feature selection. Appl Soft Comput 62:441\u2013453. https:\/\/doi.org\/10.1016\/j.asoc.2017.11.006","journal-title":"Appl Soft Comput"},{"key":"3304_CR36","doi-asserted-by":"publisher","unstructured":"Majhi, S. K. (2019). Fuzzy clustering algorithm based on modified whale optimization algorithm for automobile insurance fraud detection. Evolutionary Intelligence, 0123456789. https:\/\/doi.org\/https:\/\/doi.org\/10.1007\/s12065-019-00260-3","DOI":"10.1007\/s12065-019-00260-3"},{"issue":"2","key":"3304_CR37","doi-asserted-by":"publisher","first-page":"1679","DOI":"10.1016\/j.asoc.2010.04.024","volume":"11","author":"R Mallipeddi","year":"2011","unstructured":"Mallipeddi R, Suganthan PN, Pan QK, Tasgetiren MF (2011) Differential evolution algorithm with ensemble of parameters and mutation strategies. Appl Soft Comput J 11(2):1679\u20131696. https:\/\/doi.org\/10.1016\/j.asoc.2010.04.024","journal-title":"Appl Soft Comput J"},{"key":"3304_CR38","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\u2212inspired heuristic paradigm. Knowl-Based Syst 89:228\u2013249. https:\/\/doi.org\/10.1016\/j.knosys.2015.07.006","journal-title":"Knowl-Based Syst"},{"key":"3304_CR39","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":"3304_CR40","doi-asserted-by":"publisher","first-page":"129","DOI":"10.1016\/j.eswa.2017.07.037","volume":"89","author":"U Mlakar","year":"2017","unstructured":"Mlakar U, Fister I, Brest J, Poto\u010dnik B (2017) Multi-objective differential evolution for feature selection in facial expression recognition systems. Expert Syst Appl 89:129\u2013137. https:\/\/doi.org\/10.1016\/j.eswa.2017.07.037","journal-title":"Expert Syst Appl"},{"key":"3304_CR41","doi-asserted-by":"publisher","unstructured":"Mohamed AW, Hadi AA, Fattouh AM, Jambi KM (2017) LSHADE with semi-parameter adaptation hybrid with CMA-ES for solving CEC 2017 benchmark problems. I: 2017 IEEE Congress on Evolutionary Computation, CEC 2017\u2014Proceedings, 145\u2013152. https:\/\/doi.org\/https:\/\/doi.org\/10.1109\/CEC.2017.7969307","DOI":"10.1109\/CEC.2017.7969307"},{"issue":"23","key":"3304_CR42","doi-asserted-by":"publisher","first-page":"24931","DOI":"10.1007\/s11042-017-4638-5","volume":"76","author":"A Mostafa","year":"2017","unstructured":"Mostafa A, Hassanien AE, Houseni M, Hefny H (2017) Liver segmentation in MRI images based on whale optimization algorithm. Multimedia Tools Appl 76(23):24931\u201324954. https:\/\/doi.org\/10.1007\/s11042-017-4638-5","journal-title":"Multimedia Tools Appl"},{"issue":"3","key":"3304_CR43","doi-asserted-by":"publisher","first-page":"243","DOI":"10.1016\/j.jcde.2019.02.002","volume":"6","author":"S Mostafa Bozorgi","year":"2019","unstructured":"Mostafa Bozorgi S, Yazdani S (2019) IWOA: an improved whale optimization algorithm for optimization problems. J Comput Design Eng 6(3):243\u2013259. https:\/\/doi.org\/10.1016\/j.jcde.2019.02.002","journal-title":"J Comput Design Eng"},{"key":"3304_CR44","doi-asserted-by":"publisher","unstructured":"Muangkote N, Sunat K, Chiewchanwattana S (2017) R r-cr -IJADE: An efficient differential evolution algorithm for multilevel image thresholding. Expert Syst Appl 90:272\u2013289. https:\/\/doi.org\/10.1016\/j.eswa.2017.08.029.","DOI":"10.1016\/j.eswa.2017.08.029"},{"issue":"7","key":"3304_CR45","doi-asserted-by":"publisher","first-page":"1657","DOI":"10.1007\/s10489-017-1016-y","volume":"48","author":"S Nama","year":"2018","unstructured":"Nama S, Saha AK (2018a) A new hybrid differential evolution algorithm with self-adaptation for function optimization. Appl Intell 48(7):1657\u20131671. https:\/\/doi.org\/10.1007\/s10489-017-1016-y","journal-title":"Appl Intell"},{"issue":"2","key":"3304_CR46","doi-asserted-by":"publisher","first-page":"103","DOI":"10.5267\/j.dsl.2017.6.006","volume":"7","author":"S Nama","year":"2018","unstructured":"Nama S, Saha AK (2018b) An ensemble symbiosis organisms search algorithm and its application to real world problems. Decision Sci Lett 7(2):103\u2013118. https:\/\/doi.org\/10.5267\/j.dsl.2017.6.006","journal-title":"Decision Sci Lett"},{"key":"3304_CR47","doi-asserted-by":"publisher","unstructured":"Nama, S., Saha, A. K., & Sharma, S. (2020). A novel improved symbiotic organisms search algorithm. Computational Intelligence, 1\u201331. https:\/\/doi.org\/https:\/\/doi.org\/10.1111\/coin.12290","DOI":"10.1111\/coin.12290"},{"issue":"1\u20132","key":"3304_CR48","doi-asserted-by":"publisher","first-page":"61","DOI":"10.1007\/s10462-009-9137-2","volume":"33","author":"F Neri","year":"2009","unstructured":"Neri F, Tirronen V (2009) Recent advances in differential evolution: a survey and experimental analysis. Artif Intell Rev 33(1\u20132):61\u2013106. https:\/\/doi.org\/10.1007\/s10462-009-9137-2","journal-title":"Artif Intell Rev"},{"key":"3304_CR49","doi-asserted-by":"publisher","DOI":"10.1016\/j.energy.2018.05.052","author":"L Peng","year":"2018","unstructured":"Peng L, Liu S, Liu R, Wang L (2018) Effective long short-term memory with differential evolution algorithm for electricity price prediction. Energy. https:\/\/doi.org\/10.1016\/j.energy.2018.05.052","journal-title":"Energy"},{"key":"3304_CR50","doi-asserted-by":"publisher","first-page":"105520","DOI":"10.1016\/j.asoc.2019.105520","volume":"81","author":"M Petrovi\u0107","year":"2019","unstructured":"Petrovi\u0107 M, Miljkovi\u0107 Z, Joki\u0107 A (2019) A novel methodology for optimal single mobile robot scheduling using whale optimization algorithm. Appl Soft Comput J 81:105520. https:\/\/doi.org\/10.1016\/j.asoc.2019.105520","journal-title":"Appl Soft Comput J"},{"issue":"2","key":"3304_CR51","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(2):398\u2013417. https:\/\/doi.org\/10.1109\/TEVC.2008.927706","journal-title":"IEEE Trans Evol Comput"},{"issue":"3","key":"3304_CR52","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 Design 43(3):303\u2013315. https:\/\/doi.org\/10.1016\/j.cad.2010.12.015","journal-title":"CAD Comput Aided Design"},{"key":"3304_CR53","doi-asserted-by":"publisher","unstructured":"Rodrigues LR, Gomes JPP, Neto ARR, Souza AH (2018) A modified symbiotic organisms search algorithm applied to flow shop scheduling problems. In: 2018 IEEE Congress on Evolutionary Computation, CEC 2018\u2014Proceedings, 1. https:\/\/doi.org\/10.1109\/CEC.2018.8477846","DOI":"10.1109\/CEC.2018.8477846"},{"key":"3304_CR54","doi-asserted-by":"publisher","first-page":"747","DOI":"10.1016\/j.asoc.2018.07.039","volume":"71","author":"A Sadollah","year":"2018","unstructured":"Sadollah A, Sayyaadi H, Yadav A (2018) A dynamic metaheuristic optimization model inspired by biological nervous systems: neural network algorithm. Appl Soft Comput J 71:747\u2013782. https:\/\/doi.org\/10.1016\/j.asoc.2018.07.039","journal-title":"Appl Soft Comput J"},{"issue":"11","key":"3304_CR55","doi-asserted-by":"publisher","first-page":"3797","DOI":"10.1007\/s00500-017-2597-4","volume":"22","author":"S Saha","year":"2018","unstructured":"Saha S, Mukherjee V (2018) A novel chaos-integrated symbiotic organisms search algorithm for global optimization. Soft Comput 22(11):3797\u20133816. https:\/\/doi.org\/10.1007\/s00500-017-2597-4","journal-title":"Soft Comput"},{"key":"3304_CR56","doi-asserted-by":"publisher","first-page":"366","DOI":"10.1016\/j.energy.2016.07.056","volume":"113","author":"DC Secui","year":"2016","unstructured":"Secui DC (2016) A modified symbiotic organisms search algorithm for large scale economic dispatch problem with valve\u2212point effects. Energy 113:366\u2013384. https:\/\/doi.org\/10.1016\/j.energy.2016.07.056","journal-title":"Energy"},{"key":"3304_CR57","doi-asserted-by":"publisher","DOI":"10.1007\/s00500-019-04234-6","author":"S Sharma","year":"2019","unstructured":"Sharma S, Saha AK (2019) m-MBOA\u202f: a novel butterfly optimization algorithm enhanced with mutualism scheme. Soft Comput. https:\/\/doi.org\/10.1007\/s00500-019-04234-6","journal-title":"Soft Comput"},{"key":"3304_CR58","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-020-10053-x","author":"S Sharma","year":"2020","unstructured":"Sharma S, Saha AK (2020) MPBOA\u2014a novel hybrid butterfly optimization algorithm with symbiosis organisms search for global optimization and image segmentation. Multimedia Tools Appl. https:\/\/doi.org\/10.1007\/s11042-020-10053-x","journal-title":"Multimedia Tools Appl"},{"issue":"4","key":"3304_CR59","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\u2014a simple and efficient heuristic for global optimization over continuous spaces. J Global Optim 11(4):341\u2013359. https:\/\/doi.org\/10.1023\/a:1008202821328","journal-title":"J Global Optim"},{"key":"3304_CR60","doi-asserted-by":"publisher","unstructured":"Sun, W., & Zhang, C. (2018). Analysis and forecasting of the carbon price using multi\u2014resolution singular value decomposition and extreme learning machine optimized by adaptive whale optimization algorithm. Applied Energy, 1354\u20131371. https:\/\/doi.org\/https:\/\/doi.org\/10.1016\/j.apenergy.2018.09.118","DOI":"10.1016\/j.apenergy.2018.09.118"},{"key":"3304_CR61","doi-asserted-by":"publisher","first-page":"563","DOI":"10.1016\/j.eswa.2018.08.027","volume":"114","author":"Y Sun","year":"2018","unstructured":"Sun Y, Wang X, Chen Y, Liu Z (2018) A modified whale optimization algorithm for largE\u2212scale global optimization problems. Expert Syst Appl 114:563\u2013577. https:\/\/doi.org\/10.1016\/j.eswa.2018.08.027","journal-title":"Expert Syst Appl"},{"key":"3304_CR62","doi-asserted-by":"publisher","unstructured":"Sun, Y., Yang, T., & Liu, Z. (2019). A whale optimization algorithm based on quadratic interpolation for high-dimensional global optimization problems. Applied Soft Computing Journal, 85. https:\/\/doi.org\/https:\/\/doi.org\/10.1016\/j.asoc.2019.105744","DOI":"10.1016\/j.asoc.2019.105744"},{"key":"3304_CR63","doi-asserted-by":"publisher","unstructured":"Tanabe R, Fukunaga AS (2014) Improving the search performance of SHADE using linear population size reduction. In: Proceedings of the 2014 IEEE congress on evolutionary computation, CEC 2014, 1658\u20131665. https:\/\/doi.org\/10.1109\/CEC.2014.6900380","DOI":"10.1109\/CEC.2014.6900380"},{"key":"3304_CR64","doi-asserted-by":"publisher","unstructured":"Tanabe R, Fukunaga A (2013) Success-history based parameter adaptation for differential evolution. In: 2013 IEEE congress on evolutionary computation, CEC 2013, 3, 71\u201378. https:\/\/doi.org\/https:\/\/doi.org\/10.1109\/CEC.2013.6557555","DOI":"10.1109\/CEC.2013.6557555"},{"key":"3304_CR65","doi-asserted-by":"publisher","unstructured":"Tang C, Sun W, Wu W, Xue M. (2019) A hybrid improved whale optimization algorithm. In: IEEE 15th international conference on control and automation (ICCA). https:\/\/doi.org\/https:\/\/doi.org\/10.1109\/icca.2019.8900003","DOI":"10.1109\/icca.2019.8900003"},{"issue":"1","key":"3304_CR66","doi-asserted-by":"publisher","first-page":"67","DOI":"10.1109\/4235.585893","volume":"1","author":"DH Wolpert","year":"1997","unstructured":"Wolpert DH, Macready WG (1997) No free lunch theorems for optimization. IEEE Trans Evol Comput 1(1):67\u201382. https:\/\/doi.org\/10.1109\/4235.585893","journal-title":"IEEE Trans Evol Comput"},{"issue":"23","key":"3304_CR67","doi-asserted-by":"publisher","first-page":"2795","DOI":"10.3390\/rs11232795","volume":"11","author":"G Xiong","year":"2019","unstructured":"Xiong G, Zhang J, Shi D, Zhu L, Yuan X, Yao G (2019) Modified search strategies assisted crossover whale optimization algorithm with selection operator for parameter extraction of solar photovoltaic models. Remote Sens 11(23):2795. https:\/\/doi.org\/10.3390\/rs11232795","journal-title":"Remote Sens"},{"key":"3304_CR68","doi-asserted-by":"publisher","first-page":"36642","DOI":"10.1109\/ACCESS.2019.2905009","volume":"7","author":"Q Zhang","year":"2019","unstructured":"Zhang Q, Liu L (2019) Whale optimization algorithm based on lamarckian learning for global optimization problems. IEEE Access 7:36642\u201336666. https:\/\/doi.org\/10.1109\/ACCESS.2019.2905009","journal-title":"IEEE Access"},{"key":"3304_CR69","doi-asserted-by":"publisher","unstructured":"Zorarpac\u0131 E, \u00d6zel SA (2016) A hybrid approach of differential evolution and artificial bee colony for feature selection. Expert Syst Appl 62, 91\u2013103 https:\/\/doi.org\/10.1016\/j.eswa.2016.06.004.","DOI":"10.1016\/j.eswa.2016.06.004"}],"container-title":["Journal of Ambient Intelligence and Humanized Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12652-021-03304-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s12652-021-03304-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12652-021-03304-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,13]],"date-time":"2023-01-13T18:30:25Z","timestamp":1673634625000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s12652-021-03304-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,5,28]]},"references-count":69,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2023,1]]}},"alternative-id":["3304"],"URL":"https:\/\/doi.org\/10.1007\/s12652-021-03304-8","relation":{},"ISSN":["1868-5137","1868-5145"],"issn-type":[{"value":"1868-5137","type":"print"},{"value":"1868-5145","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,5,28]]},"assertion":[{"value":"16 October 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"1 May 2021","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"28 May 2021","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}