{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,18]],"date-time":"2026-05-18T10:08:31Z","timestamp":1779098911482,"version":"3.51.4"},"reference-count":157,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"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":["Appl Intell"],"published-print":{"date-parts":[[2024,1]]},"DOI":"10.1007\/s10489-023-05073-7","type":"journal-article","created":{"date-parts":[[2024,1,27]],"date-time":"2024-01-27T00:07:03Z","timestamp":1706314023000},"page":"2031-2083","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["A Memetic Approach to Multi-Disciplinary Design and Numerical Optimization Problems using Intensify Slime Mould Optimizer"],"prefix":"10.1007","volume":"54","author":[{"given":"Shivani","family":"Sehgal","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Aman","family":"Ganesh","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Vikram Kumar","family":"Kamboj","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"O. P.","family":"Malik","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,1,27]]},"reference":[{"key":"5073_CR1","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-015-1942-8","author":"WY Lin","year":"2016","unstructured":"Lin WY (2016) A novel 3D fruit fly optimization algorithm and its applications in economics. Neural Comput Appl. https:\/\/doi.org\/10.1007\/s00521-015-1942-8","journal-title":"Neural Comput Appl"},{"key":"5073_CR2","doi-asserted-by":"publisher","DOI":"10.1155\/2018\/9174568","author":"Y Cheng","year":"2018","unstructured":"Cheng Y, Zhao S, Cheng B, Hou S, Shi Y, Chen J (2018) Modeling and optimization for collaborative business process towards IoT applications. Mob Inf Syst. https:\/\/doi.org\/10.1155\/2018\/9174568","journal-title":"Mob Inf Syst"},{"key":"5073_CR3","doi-asserted-by":"publisher","first-page":"556","DOI":"10.1109\/TSMC.2016.2606440","volume":"48","author":"X Wang","year":"2018","unstructured":"Wang X, Choi TM, Liu H, Yue X (2018) A novel hybrid ant colony optimization algorithm for emergency transportation problems during post-disaster scenarios. IEEE Trans Syst Man Cybern Syst 48:556. https:\/\/doi.org\/10.1109\/TSMC.2016.2606440","journal-title":"IEEE Trans Syst Man Cybern Syst"},{"key":"5073_CR4","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4757-5331-8_10","volume-title":"Global optimization in engineering design. Nonconvex optimization and its applications","author":"I Quesada","year":"1996","unstructured":"Quesada I, Grossmann IE (1996) Alternative bounding approximations for the global optimization of various engineering design problems. In: Grossmann IE (ed) Global optimization in engineering design. Nonconvex optimization and its applications, vol 9. Springer, Boston, MA. https:\/\/doi.org\/10.1007\/978-1-4757-5331-8_10"},{"issue":"1","key":"5073_CR5","doi-asserted-by":"publisher","first-page":"60","DOI":"10.1080\/0305215X.2016.1164855","volume":"49","author":"R Venkata Rao","year":"2017","unstructured":"Venkata Rao R, Waghmare GG (2017) A new optimization algorithm for solving complex constrained design optimization problems. Eng Optim 49(1):60\u201383. https:\/\/doi.org\/10.1080\/0305215X.2016.1164855","journal-title":"Eng Optim"},{"key":"5073_CR6","doi-asserted-by":"publisher","DOI":"10.1109\/access.2020.3001151","author":"E-SM El-Kenawy","year":"2020","unstructured":"El-Kenawy E-SM, Eid MM, Saber M, Ibrahim A (2020) MbGWO-SFS: Modified Binary Grey Wolf Optimizer Based on Stochastic Fractal Search for Feature Selection. IEEE Access. https:\/\/doi.org\/10.1109\/access.2020.3001151","journal-title":"IEEE Access"},{"key":"5073_CR7","doi-asserted-by":"publisher","DOI":"10.1007\/s10845-015-1039-3","author":"M Nouiri","year":"2018","unstructured":"Nouiri M, Bekrar A, Jemai A, Niar S, Ammari AC (2018) An effective and distributed particle swarm optimization algorithm for flexible job-shop scheduling problem. J Intell Manuf. https:\/\/doi.org\/10.1007\/s10845-015-1039-3","journal-title":"J Intell Manuf"},{"key":"5073_CR8","doi-asserted-by":"publisher","DOI":"10.1016\/j.energy.2018.07.200","author":"Y Li","year":"2018","unstructured":"Li Y, Wang J, Zhao D, Li G, Chen C (2018) A two-stage approach for combined heat and power economic emission dispatch: Combining multi-objective optimization with integrated decision making. Energy. https:\/\/doi.org\/10.1016\/j.energy.2018.07.200","journal-title":"Energy"},{"key":"5073_CR9","doi-asserted-by":"publisher","unstructured":"Yousri D, Fathy A, Babu TS (2020) Recent methodology based Harris Hawks optimizer for designing load frequency control incorporated in multi-interconnected renewable energy plants.\u00a0Sustain Energy, Grids Netw 22. https:\/\/doi.org\/10.1016\/j.segan.2020.100352","DOI":"10.1016\/j.segan.2020.100352"},{"key":"5073_CR10","doi-asserted-by":"publisher","DOI":"10.3934\/energy.2017.5.798","author":"R Al-Hajj","year":"2017","unstructured":"Al-Hajj R, Assi A (2017) Estimating solar irradiance using genetic programming technique and meteorological records. AIMS Energy. https:\/\/doi.org\/10.3934\/energy.2017.5.798","journal-title":"AIMS Energy"},{"key":"5073_CR11","doi-asserted-by":"publisher","unstructured":"Al-Hajj R, Assi A (2016) An evolutionary computing approach for estimating global solar radiation. IEEE International Conference on Renewable Energy Research and Applications (ICRERA), Birmingham, UK, pp 285\u2013290. https:\/\/doi.org\/10.1109\/icrera.2016.7884553\u00a0","DOI":"10.1109\/icrera.2016.7884553"},{"key":"5073_CR12","doi-asserted-by":"publisher","unstructured":"Wehrens R, Buydens L (2006) Classical and nonclassical optimization methods. In: Encyclopedia of Analytical Chemistry. https:\/\/doi.org\/10.1002\/9780470027318.a5203","DOI":"10.1002\/9780470027318.a5203"},{"key":"5073_CR13","doi-asserted-by":"publisher","unstructured":"Steffan N, Heydt G (2012) Quadratic programming and related techniques for the calculation of locational marginal prices in distribution systems. https:\/\/doi.org\/10.1109\/NAPS.2012.6336310","DOI":"10.1109\/NAPS.2012.6336310"},{"key":"5073_CR14","doi-asserted-by":"publisher","first-page":"25","DOI":"10.1016\/j.knosys.2017.12.037","volume":"145","author":"M Mafarja","year":"2018","unstructured":"Mafarja M et al (2018) Evolutionary Population Dynamics and Grasshopper Optimization approaches for feature selection problems. Knowledge-Based Syst 145:25\u201345. https:\/\/doi.org\/10.1016\/j.knosys.2017.12.037","journal-title":"Knowledge-Based Syst"},{"issue":"1","key":"5073_CR15","doi-asserted-by":"publisher","first-page":"57","DOI":"10.1007\/s00521-015-2037-2","volume":"28","author":"AA Heidari","year":"2017","unstructured":"Heidari AA, Ali Abbaspour R, RezaeeJordehi A (2017) An efficient chaotic water cycle algorithm for optimization tasks. Neural Comput Appl 28(1):57\u201385. https:\/\/doi.org\/10.1007\/s00521-015-2037-2","journal-title":"Neural Comput Appl"},{"key":"5073_CR16","doi-asserted-by":"publisher","first-page":"323","DOI":"10.1016\/j.future.2020.03.055","volume":"111","author":"S Li","year":"2020","unstructured":"Li S, Chen H, Wang M, Heidari AA, Mirjalili S (2020) Slime mould algorithm: A new method for stochastic optimization. Futur Gener Comput Syst 111:323. https:\/\/doi.org\/10.1016\/j.future.2020.03.055","journal-title":"Futur Gener Comput Syst"},{"key":"5073_CR17","doi-asserted-by":"publisher","unstructured":"Kennedy J, Eberhart R (1995) Particle swarm optimization. Proceedings of ICNN\u201995 -International Conference on Neural Networks 4:1942\u20131948. https:\/\/doi.org\/10.1109\/ICNN.1995.488968","DOI":"10.1109\/ICNN.1995.488968"},{"key":"5073_CR18","doi-asserted-by":"publisher","first-page":"148378","DOI":"10.1109\/ACCESS.2020.3015892","volume":"8","author":"MM Fouad","year":"2020","unstructured":"Fouad MM, El-Desouky AI, Al-Hajj R, El-Kenawy ESM (2020) Dynamic Group-Based Cooperative Optimization Algorithm. IEEE Access 8:148378\u2013148403. https:\/\/doi.org\/10.1109\/ACCESS.2020.3015892","journal-title":"IEEE Access"},{"key":"5073_CR19","doi-asserted-by":"publisher","first-page":"103731","DOI":"10.1016\/j.engappai.2020.103731","volume":"94","author":"EH Houssein","year":"2020","unstructured":"Houssein EH, Saad MR, Hashim FA, Shaban H, Hassaballah M (2020) L\u00e9vy flight distribution: A new metaheuristic algorithm for solving engineering optimization problems. Eng Appl Artif Intell 94:103731. https:\/\/doi.org\/10.1016\/j.engappai.2020.103731","journal-title":"Eng Appl Artif Intell"},{"key":"5073_CR20","doi-asserted-by":"publisher","unstructured":"Khatri A, Gaba A, Rana K, Kumar V (2020) A novel life choice-based optimizer. Soft Computing 24. https:\/\/doi.org\/10.1007\/s00500-019-04443-z","DOI":"10.1007\/s00500-019-04443-z"},{"key":"5073_CR21","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":"5073_CR22","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":"5073_CR23","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) Knowledge-Based Systems Moth-flame optimization algorithm\u202f: A novel nature-inspired heuristic paradigm. Knowledge-Based Syst 89:228\u2013249. https:\/\/doi.org\/10.1016\/j.knosys.2015.07.006","journal-title":"Knowledge-Based Syst"},{"issue":"1","key":"5073_CR24","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 X-S, Alavi AH (2013) Cuckoo search algorithm: a metaheuristic approach to solve structural optimization problems. Eng Comput 29(1):17\u201335. https:\/\/doi.org\/10.1007\/s00366-011-0241-y","journal-title":"Eng Comput"},{"key":"5073_CR25","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":"5073_CR26","doi-asserted-by":"publisher","unstructured":"Karaboga D, Basturk B (2007) Artificial Bee Colony (ABC) optimization algorithm for solving constrained optimization problems, vol 4529. https:\/\/doi.org\/10.1007\/978-3-540-72950-1_77","DOI":"10.1007\/978-3-540-72950-1_77"},{"issue":"4598","key":"5073_CR27","doi-asserted-by":"publisher","first-page":"671","DOI":"10.1126\/science.220.4598.671","volume":"220","author":"S Kirkpatrick","year":"1983","unstructured":"Kirkpatrick S, Gelatt CD, Vecchi MP (1983) Optimization by simulated annealing. Science 220(4598):671\u2013680. https:\/\/doi.org\/10.1126\/science.220.4598.671","journal-title":"Science"},{"key":"5073_CR28","doi-asserted-by":"publisher","DOI":"10.1007\/s10489-020-01727-y","author":"MH Qais","year":"2020","unstructured":"Qais MH, Hasanien HM, Alghuwainem S (2020) Transient search optimization: a new meta-heuristic optimization algorithm. Appl Intell. https:\/\/doi.org\/10.1007\/s10489-020-01727-y","journal-title":"Appl Intell"},{"key":"5073_CR29","doi-asserted-by":"publisher","first-page":"1722","DOI":"10.1016\/j.istruc.2020.07.058","volume":"27","author":"A Kaveh","year":"2020","unstructured":"Kaveh A, Khanzadi M, RastegarMoghaddam M (2020) Billiards-inspired optimization algorithm; a new meta-heuristic method. Structures 27:1722\u20131739. https:\/\/doi.org\/10.1016\/j.istruc.2020.07.058","journal-title":"Structures"},{"issue":"2","key":"5073_CR30","doi-asserted-by":"publisher","first-page":"478","DOI":"10.3745\/JIPS.04.0168","volume":"16","author":"Y Liu","year":"2020","unstructured":"Liu Y, Li R (2020) PSA: a photon search algorithm. J Inf Process Syst 16(2):478\u2013493. https:\/\/doi.org\/10.3745\/JIPS.04.0168","journal-title":"J Inf Process Syst"},{"key":"5073_CR31","doi-asserted-by":"publisher","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. https:\/\/doi.org\/10.1016\/j.future.2019.07.015","journal-title":"Futur Gener Comput Syst"},{"issue":"2","key":"5073_CR32","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(2):495\u2013513. https:\/\/doi.org\/10.1007\/s00521-015-1870-7","journal-title":"Neural Comput Appl"},{"key":"5073_CR33","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. Knowledge-Based Syst 96:120\u2013133. https:\/\/doi.org\/10.1016\/j.knosys.2015.12.022","journal-title":"Knowledge-Based Syst"},{"key":"5073_CR34","doi-asserted-by":"publisher","DOI":"10.1007\/s00707-009-0270-4","author":"A Kaveh","year":"2010","unstructured":"Kaveh A, Talatahari S (2010) A novel heuristic optimization method: Charged system search. Acta Mech. https:\/\/doi.org\/10.1007\/s00707-009-0270-4","journal-title":"Acta Mech"},{"issue":"13","key":"5073_CR35","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(13):2232\u20132248. https:\/\/doi.org\/10.1016\/j.ins.2009.03.004","journal-title":"Inf Sci (Ny)"},{"key":"5073_CR36","doi-asserted-by":"publisher","first-page":"8","DOI":"10.1016\/j.swevo.2015.07.002","volume":"26","author":"H Abedinpourshotorban","year":"2016","unstructured":"Abedinpourshotorban H, MariyamShamsuddin S, Beheshti Z, Jawawi DNA (2016) \u201cElectromagnetic field optimization: A physics-inspired metaheuristic optimization algorithm\u201d, Swarm Evol. Comput 26:8\u201322. https:\/\/doi.org\/10.1016\/j.swevo.2015.07.002","journal-title":"Comput"},{"key":"5073_CR37","doi-asserted-by":"publisher","DOI":"10.2528\/PIER07082403","author":"RA Formato","year":"2007","unstructured":"Formato RA (2007) Central force optimization: A new metaheuristic with applications in applied electromagnetics. Prog Electromagn Res. https:\/\/doi.org\/10.2528\/PIER07082403","journal-title":"Prog Electromagn Res"},{"key":"5073_CR38","doi-asserted-by":"publisher","DOI":"10.1177\/003754970107600201","author":"ZW Geem","year":"2001","unstructured":"Geem ZW, Kim JH, Loganathan GV (2001) A new heuristic optimization algorithm: Harmony search. Simulation. https:\/\/doi.org\/10.1177\/003754970107600201","journal-title":"Simulation"},{"key":"5073_CR39","doi-asserted-by":"publisher","DOI":"10.1016\/j.compchemeng.2017.01.046","author":"A Tabari","year":"2017","unstructured":"Tabari A, Ahmad A (2017) A new optimization method: Electro-Search algorithm. Comput Chem Eng. https:\/\/doi.org\/10.1016\/j.compchemeng.2017.01.046","journal-title":"Comput Chem Eng"},{"issue":"3","key":"5073_CR40","doi-asserted-by":"publisher","first-page":"190","DOI":"10.1287\/ijoc.1.3.190","volume":"1","author":"F Glover","year":"1989","unstructured":"Glover F (1989) Tabu Search - Part I. Orsa J Comput 1(3):190\u2013206","journal-title":"Orsa J Comput"},{"key":"5073_CR41","doi-asserted-by":"publisher","DOI":"10.1109\/TEVC.2009.2011992","author":"S He","year":"2009","unstructured":"He S, Wu QH, Saunders JR (2009) Group search optimizer: An optimization algorithm inspired by animal searching behavior. IEEE Trans Evol Comput. https:\/\/doi.org\/10.1109\/TEVC.2009.2011992","journal-title":"IEEE Trans Evol Comput"},{"issue":"1","key":"5073_CR42","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.ins.2011.08.006","volume":"183","author":"RV Rao","year":"2012","unstructured":"Rao RV, Savsani VJ, Vakharia DP (2012) Teaching-Learning-Based Optimization: An optimization method for continuous non-linear large scale problems. Inf Sci (Ny) 183(1):1\u201315. https:\/\/doi.org\/10.1016\/j.ins.2011.08.006","journal-title":"Inf Sci (Ny)"},{"issue":"1","key":"5073_CR43","doi-asserted-by":"publisher","first-page":"66","DOI":"10.1038\/scientificamerican0792-66","volume":"267","author":"JH Holland","year":"1992","unstructured":"Holland JH (1992) Genetic algorithms. Sci Am 267(1):66\u201372. https:\/\/doi.org\/10.1038\/scientificamerican0792-66","journal-title":"Sci Am"},{"key":"5073_CR44","doi-asserted-by":"publisher","DOI":"10.1162\/106365603321828970","author":"N Hansen","year":"2003","unstructured":"Hansen N, M\u00fcller SD, Koumoutsakos P (2003) Reducing the time complexity of the derandomized evolution strategy with covariance matrix adaptation (CMA-ES). Evol Comput. https:\/\/doi.org\/10.1162\/106365603321828970","journal-title":"Evol Comput"},{"issue":"2","key":"5073_CR45","doi-asserted-by":"publisher","first-page":"82","DOI":"10.1109\/4235.771163","volume":"3","author":"X Yao","year":"1999","unstructured":"Yao X, Liu Y, Lin G (1999) Evolutionary Programming Made Faster. IEEE Trans Evol Computat 3(2):82\u2013102. https:\/\/doi.org\/10.1109\/4235.771163","journal-title":"IEEE Trans Evol Computat"},{"key":"5073_CR46","doi-asserted-by":"publisher","DOI":"10.1023\/A:1008202821328","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. https:\/\/doi.org\/10.1023\/A:1008202821328","journal-title":"J Glob Optim"},{"issue":"6","key":"5073_CR47","doi-asserted-by":"publisher","first-page":"702","DOI":"10.1109\/TEVC.2008.919004","volume":"12","author":"D Simon","year":"2008","unstructured":"Simon D (2008) Biogeography-based optimization. IEEE Trans Evol Comput 12(6):702\u2013713. https:\/\/doi.org\/10.1109\/TEVC.2008.919004","journal-title":"IEEE Trans Evol Comput"},{"issue":"2","key":"5073_CR48","doi-asserted-by":"publisher","first-page":"87","DOI":"10.1007\/BF00175355","volume":"4","author":"JR Koza","year":"1994","unstructured":"Koza JR (1994) Genetic programming as a means for programming computers by natural selection. Stat Comput 4(2):87\u2013112. https:\/\/doi.org\/10.1007\/BF00175355","journal-title":"Stat Comput"},{"key":"5073_CR49","doi-asserted-by":"publisher","unstructured":"Banerjee N, Mukhopadhyay S (2019) HC-PSOGWO: hybrid crossover oriented PSO and GWO based co-evolution for global optimization. 2019 IEEE Region 10 Symposium (TENSYMP), pp 162\u2013167. https:\/\/doi.org\/10.1109\/TENSYMP46218.2019.8971231","DOI":"10.1109\/TENSYMP46218.2019.8971231"},{"key":"5073_CR50","doi-asserted-by":"publisher","first-page":"124872","DOI":"10.1016\/j.amc.2019.124872","volume":"369","author":"H Chen","year":"2020","unstructured":"Chen H, Wang M, Zhao X (2020) A multi-strategy enhanced sine cosine algorithm for global optimization and constrained practical engineering problems. Appl Math Comput 369:124872. https:\/\/doi.org\/10.1016\/j.amc.2019.124872","journal-title":"Appl Math Comput"},{"issue":"1","key":"5073_CR51","doi-asserted-by":"publisher","first-page":"509","DOI":"10.1007\/s00366-019-00837-7","volume":"37","author":"A Seyyedabbasi","year":"2021","unstructured":"Seyyedabbasi A, Kiani F (2021) I-GWO and Ex-GWO: improved algorithms of the Grey Wolf Optimizer to solve global optimization problems. Eng Comput 37(1):509\u2013532. https:\/\/doi.org\/10.1007\/s00366-019-00837-7","journal-title":"Eng Comput"},{"key":"5073_CR52","doi-asserted-by":"publisher","unstructured":"Xiao B, Wang R, Xu Y, Wang J, Song W, Deng Y (2019) Simplified salp swarm algorithm. 2019 IEEE International Conference on Artificial Intelligence and Computer Applications (ICAICA), pp 226\u2013230. https:\/\/doi.org\/10.1109\/ICAICA.2019.8873515","DOI":"10.1109\/ICAICA.2019.8873515"},{"key":"5073_CR53","doi-asserted-by":"publisher","first-page":"70","DOI":"10.1016\/j.swevo.2019.01.003","volume":"45","author":"X Chen","year":"2019","unstructured":"Chen X, Tianfield H, Li K (2019) Self-adaptive differential artificial bee colony algorithm for global optimization problems. Swarm Evol Comput 45:70\u201391. https:\/\/doi.org\/10.1016\/j.swevo.2019.01.003","journal-title":"Swarm Evol Comput"},{"key":"5073_CR54","doi-asserted-by":"publisher","DOI":"10.1007\/s00366-019-00846-6","author":"GG Tejani","year":"2019","unstructured":"Tejani GG, Kumar S, Gandomi AH (2019) Multi-objective heat transfer search algorithm for truss optimization. Eng Comput. https:\/\/doi.org\/10.1007\/s00366-019-00846-6","journal-title":"Eng Comput"},{"key":"5073_CR55","doi-asserted-by":"publisher","first-page":"112838","DOI":"10.1016\/j.eswa.2019.112838","volume":"139","author":"A Yimit","year":"2020","unstructured":"Yimit A, Iigura K, Hagihara Y (2020) Refined selfish herd optimizer for global optimization problems. Expert Syst Appl 139:112838. https:\/\/doi.org\/10.1016\/j.eswa.2019.112838","journal-title":"Expert Syst Appl"},{"issue":"3","key":"5073_CR56","first-page":"243","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 Des Eng 6(3):243\u2013259","journal-title":"J Comput Des Eng"},{"key":"5073_CR57","doi-asserted-by":"publisher","first-page":"19074","DOI":"10.1109\/ACCESS.2020.2968064","volume":"8","author":"DA Muhammed","year":"2020","unstructured":"Muhammed DA, Saeed SAM, Rashid TA (2020) Improved Fitness-Dependent Optimizer Algorithm. IEEE Access 8:19074\u201319088. https:\/\/doi.org\/10.1109\/ACCESS.2020.2968064","journal-title":"IEEE Access"},{"key":"5073_CR58","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. Knowledge-Based Syst 191:105190. https:\/\/doi.org\/10.1016\/j.knosys.2019.105190","journal-title":"Knowledge-Based Syst"},{"key":"5073_CR59","doi-asserted-by":"publisher","unstructured":"Sulaiman MH, Mustaffa Z, Saari MM, Daniyal H (2020) Barnacles mating optimizer: a new bio-inspired algorithm for solving engineering optimization problems. Eng Appl Artif Intell 87. https:\/\/doi.org\/10.1016\/j.engappai.2019.103330","DOI":"10.1016\/j.engappai.2019.103330"},{"issue":"1","key":"5073_CR60","first-page":"155","volume":"10","author":"M Shahrouzi","year":"2020","unstructured":"Shahrouzi M, Salehi A (2020) Imperialist competitive learner-based optimization: a hybrid method to solve engineering problems. Int J optim civ eng 10(1):155\u2013180","journal-title":"Int J optim civ eng"},{"key":"5073_CR61","doi-asserted-by":"publisher","first-page":"113282","DOI":"10.1016\/j.eswa.2020.113282","volume":"150","author":"Z Xu","year":"2020","unstructured":"Xu Z et al (2020) Orthogonally-designed Adapted Grasshopper Optimization: A Comprehensive Analysis. Expert Syst Appl 150:113282. https:\/\/doi.org\/10.1016\/j.eswa.2020.113282","journal-title":"Expert Syst Appl"},{"key":"5073_CR62","doi-asserted-by":"publisher","unstructured":"Dhiman G, Garg M, Nagar A, Chahar V, Dehghani M (2021) A novel algorithm for global optimization: rat swarm optimizer.\u00a0J Ambient Intell Humaniz Comput 12. https:\/\/doi.org\/10.1007\/s12652-020-02580-0\u00a0","DOI":"10.1007\/s12652-020-02580-0"},{"key":"5073_CR63","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2020.105709","author":"Q Askari","year":"2020","unstructured":"Askari Q, Younas I, Saeed M (2020) Political Optimizer: A novel socio-inspired meta-heuristic for global optimization. Knowledge-Based Syst. https:\/\/doi.org\/10.1016\/j.knosys.2020.105709","journal-title":"Knowledge-Based Syst"},{"issue":"4","key":"5073_CR64","doi-asserted-by":"publisher","first-page":"1051","DOI":"10.1002\/nme.6573","volume":"122","author":"A Nandi","year":"2021","unstructured":"Nandi A, Kamboj VK (2021) A Canis lupus inspired upgraded Harris hawks optimizer for nonlinear, constrained, continuous, and discrete engineering design problem. \u00a0Int J Numer Methods Eng 122(4):1051\u20131088. https:\/\/doi.org\/10.1002\/nme.6573","journal-title":"\u00a0Int J Numer Methods Eng"},{"key":"5073_CR65","doi-asserted-by":"publisher","unstructured":"Rahkar Farshi T (2021) Battle royale optimization algorithm.\u00a0Neural Comput Applic 33. https:\/\/doi.org\/10.1007\/s00521-020-05004-4","DOI":"10.1007\/s00521-020-05004-4"},{"key":"5073_CR66","doi-asserted-by":"publisher","first-page":"103541","DOI":"10.1016\/j.engappai.2020.103541","volume":"90","author":"S Kaur","year":"2020","unstructured":"Kaur S, Awasthi LK, Sangal AL, Dhiman G (2020) Tunicate Swarm Algorithm: A new bio-inspired based metaheuristic paradigm for global optimization. Eng Appl Artif Intell 90:103541. https:\/\/doi.org\/10.1016\/j.engappai.2020.103541","journal-title":"Eng Appl Artif Intell"},{"key":"5073_CR67","doi-asserted-by":"publisher","first-page":"520","DOI":"10.1016\/j.istruc.2020.03.033","volume":"25","author":"A Kaveh","year":"2020","unstructured":"Kaveh A, DadrasEslamlou A (2020) Water strider algorithm: A new metaheuristic and applications. Structures 25:520\u2013541. https:\/\/doi.org\/10.1016\/j.istruc.2020.03.033","journal-title":"Structures"},{"issue":"1","key":"5073_CR68","doi-asserted-by":"publisher","first-page":"194","DOI":"10.1515\/comp-2020-0101","volume":"10","author":"S Debnath","year":"2020","unstructured":"Debnath S, Arif W, Baishya S (2020) Buyer inspired meta-heuristic optimization algorithm. Open Comput Sci 10(1):194\u2013219. https:\/\/doi.org\/10.1515\/comp-2020-0101","journal-title":"Open Comput Sci"},{"key":"5073_CR69","doi-asserted-by":"publisher","first-page":"106339","DOI":"10.1016\/j.asoc.2020.106339","volume":"93","author":"JS Chou","year":"2020","unstructured":"Chou JS, Nguyen NM (2020) FBI inspired meta-optimization. Appl Soft Comput J 93:106339. https:\/\/doi.org\/10.1016\/j.asoc.2020.106339","journal-title":"Appl Soft Comput J"},{"key":"5073_CR70","doi-asserted-by":"publisher","first-page":"113377","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":"5073_CR71","doi-asserted-by":"publisher","first-page":"131","DOI":"10.1016\/j.ins.2020.06.037","volume":"540","author":"I Ahmadianfar","year":"2020","unstructured":"Ahmadianfar I, Bozorg-Haddad O, Chu X (2020) Gradient-based optimizer: A new metaheuristic optimization algorithm. Inf Sci (Ny) 540:131\u2013159. https:\/\/doi.org\/10.1016\/j.ins.2020.06.037","journal-title":"Inf Sci (Ny)"},{"issue":"7","key":"5073_CR72","doi-asserted-by":"publisher","first-page":"2949","DOI":"10.1007\/s00521-020-05107-y","volume":"33","author":"L Abualigah","year":"2021","unstructured":"Abualigah L (2021) Group search optimizer: a nature-inspired meta-heuristic optimization algorithm with its results, variants, and applications. Neural Comput Applic 33(7):2949\u20132972. https:\/\/doi.org\/10.1007\/s00521-020-05107-y","journal-title":"Neural Comput Applic"},{"issue":"2","key":"5073_CR73","doi-asserted-by":"publisher","first-page":"917","DOI":"10.1007\/s10462-020-09867-w","volume":"54","author":"S Talatahari","year":"2021","unstructured":"Talatahari S, Azizi M (2021) Chaos game optimization: a novel metaheuristic algorithm. Artif Intell Rev 54(2):917\u20131004. https:\/\/doi.org\/10.1007\/s10462-020-09867-w","journal-title":"Artif Intell Rev"},{"key":"5073_CR74","doi-asserted-by":"publisher","first-page":"1743","DOI":"10.1007\/s12065-020-00451-3","volume":"14","author":"S Harifi","year":"2020","unstructured":"Harifi S, Mohammadzadeh J, Khalilian M, Ebrahimnejad S (2020) Giza Pyramids Construction: an ancient-inspired metaheuristic algorithm for optimization. Evol Intell 14:1743. https:\/\/doi.org\/10.1007\/s12065-020-00451-3","journal-title":"Evol Intell"},{"issue":"7","key":"5073_CR75","doi-asserted-by":"publisher","first-page":"2357","DOI":"10.1108\/EC-10-2019-0481","volume":"37","author":"A Kaveh","year":"2020","unstructured":"Kaveh A, Zaerreza A (2020) Shu ffl ed shepherd optimization method\u202f: a new Meta-heuristic algorithm. Eng Comp 37(7):2357\u20132389. https:\/\/doi.org\/10.1108\/EC-10-2019-0481","journal-title":"Eng Comp"},{"key":"5073_CR76","doi-asserted-by":"publisher","first-page":"100766","DOI":"10.1016\/j.swevo.2020.100766","volume":"60","author":"Z Chen","year":"2021","unstructured":"Chen Z, Liu Y, Yang Z, Fu X, Tan J, Yang X (2021) An enhanced teaching-learning-based optimization algorithm with self-adaptive and learning operators and its search bias towards origin. Swarm Evol Comput 60:100766. https:\/\/doi.org\/10.1016\/j.swevo.2020.100766","journal-title":"Swarm Evol Comput"},{"issue":"8","key":"5073_CR77","doi-asserted-by":"publisher","first-page":"1311","DOI":"10.3390\/math10081311","volume":"10","author":"R Zheng","year":"2022","unstructured":"Zheng R, Hussien AG, Jia H-M, Abualigah L, Wang S, Wu D (2022) An Improved Wild Horse Optimizer for Solving Optimization Problems. Mathematics 10(8):1311. https:\/\/doi.org\/10.3390\/math10081311","journal-title":"Mathematics"},{"key":"5073_CR78","doi-asserted-by":"publisher","first-page":"6749","DOI":"10.1007\/s00500-022-07079-8","volume":"26","author":"S Mahajan","year":"2022","unstructured":"Mahajan S, Abualigah L, Pandit AK, Al Nasar MR, Alkhazaleh HA, Altalhi M (2022) Fusion of modern meta-heuristic optimization methods using arithmetic optimization algorithm for global optimization tasks. Soft Comput 26:6749. https:\/\/doi.org\/10.1007\/s00500-022-07079-8","journal-title":"Soft Comput"},{"issue":"36","key":"5073_CR79","doi-asserted-by":"publisher","first-page":"3902","DOI":"10.1016\/j.cma.2004.09.007","volume":"194","author":"KS Lee","year":"2005","unstructured":"Lee KS, Geem ZW (2005) A new meta-heuristic algorithm for continuous engineering optimization: harmony search theory and practice. Comput Methods Appl Mech Eng 194(36):3902\u20133933. https:\/\/doi.org\/10.1016\/j.cma.2004.09.007","journal-title":"Comput Methods Appl Mech Eng"},{"issue":"1","key":"5073_CR80","doi-asserted-by":"publisher","first-page":"108","DOI":"10.1016\/j.amc.2009.03.090","volume":"214","author":"D Karaboga","year":"2009","unstructured":"Karaboga D, Akay B (2009) A comparative study of Artificial Bee Colony algorithm. Appl Math Comput 214(1):108\u2013132. https:\/\/doi.org\/10.1016\/j.amc.2009.03.090","journal-title":"Appl Math Comput"},{"key":"5073_CR81","doi-asserted-by":"publisher","unstructured":"Yang X-S, Deb S (2010) Cuckoo search via levey flights. In: 2009 world congress on nature and biologically inspired computing, NABIC 2009 - Proceedings. https:\/\/doi.org\/10.1109\/NABIC.2009.5393690","DOI":"10.1109\/NABIC.2009.5393690"},{"key":"5073_CR82","doi-asserted-by":"publisher","unstructured":"Yang X-S (2010) A new metaheuristic bat-inspired algorithm. In: Nature inspired cooperative strategies for optimization, studies in computational intelligence, vol 284. Springer, Berlin, pp 65\u201374. https:\/\/doi.org\/10.1007\/978-3-642-12538-6_6","DOI":"10.1007\/978-3-642-12538-6_6"},{"key":"5073_CR83","doi-asserted-by":"publisher","unstructured":"Yang X-S (2010) Firefly algorithm. In: Yang X-S (ed) Engineering optimization. https:\/\/doi.org\/10.1002\/9780470640425.ch17","DOI":"10.1002\/9780470640425.ch17"},{"issue":"1","key":"5073_CR84","doi-asserted-by":"publisher","first-page":"2014","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(1):2014. https:\/\/doi.org\/10.1007\/s10462-012-9328-0","journal-title":"Artif Intell Rev"},{"issue":"12","key":"5073_CR85","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(12):4831\u20134845. https:\/\/doi.org\/10.1016\/j.cnsns.2012.05.010","journal-title":"Commun Nonlinear Sci Numer Simul"},{"key":"5073_CR86","doi-asserted-by":"publisher","first-page":"240","DOI":"10.1007\/978-3-642-32894-7_27","volume-title":"Unconventional computation and natural computation","author":"XS Yang","year":"2012","unstructured":"Yang XS (2012) Flower pollination algorithm for global optimization. Unconventional computation and natural computation. Springer, Berlin Heidelberg, pp 240\u2013249. https:\/\/doi.org\/10.1007\/978-3-642-32894-7_27"},{"issue":"1","key":"5073_CR87","doi-asserted-by":"publisher","first-page":"130","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. Springer Plus 2(1):130. https:\/\/doi.org\/10.1186\/2193-1801-2-130","journal-title":"Springer Plus"},{"key":"5073_CR88","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":"5073_CR89","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":"5073_CR90","doi-asserted-by":"publisher","first-page":"5803893","DOI":"10.1155\/2016\/5803893","volume":"2016","author":"WL Lim","year":"2016","unstructured":"Lim WL, Wibowo A, Desa MI, Haron H (2016) A biogeography-based optimization algorithm hybridized with Tabu search for the quadratic assignment problem. Comput Intell Neurosci 2016:5803893. https:\/\/doi.org\/10.1155\/2016\/5803893","journal-title":"Comput Intell Neurosci"},{"issue":"113609","key":"5073_CR91","doi-asserted-by":"publisher","first-page":"2021","DOI":"10.1016\/j.cma.2020.113609","volume":"376","author":"L Abualigah","year":"2021","unstructured":"Abualigah L, Diabat A, Mirjalili S, AbdElaziz M, Gandom AH (2021) The arithmetic optimization algorithm. Comput Methods Appl Mech Eng 376(113609):2021. https:\/\/doi.org\/10.1016\/j.cma.2020.113609","journal-title":"Comput Methods Appl Mech Eng"},{"key":"5073_CR92","doi-asserted-by":"publisher","first-page":"23","DOI":"10.14810\/ijscmc.2015.4302","volume":"4","author":"A Bohre","year":"2015","unstructured":"Bohre A, Agnihotri G, Dubey M (2015) The butterfly-particle swarm optimization (Butterfly-PSO\/BF-PSO) technique and its variables. Int J Soft Comp, Math Control 4:23\u201339. https:\/\/doi.org\/10.14810\/ijscmc.2015.4302","journal-title":"Int J Soft Comp, Math Control"},{"key":"5073_CR93","doi-asserted-by":"publisher","first-page":"735","DOI":"10.1016\/j.energy.2016.03.007","volume":"103","author":"H Quan","year":"2016","unstructured":"Quan H, Srinivasan D, Khosravi A (2016) Integration of renewable generation uncertainties into stochastic unit commitment considering reserve and risk\u202f: A comparative study. Energy 103:735\u2013745. https:\/\/doi.org\/10.1016\/j.energy.2016.03.007","journal-title":"Energy"},{"issue":"4","key":"5073_CR94","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(4):28\u201339. https:\/\/doi.org\/10.1109\/MCI.2006.329691","journal-title":"IEEE Comput Intell Mag"},{"key":"5073_CR95","doi-asserted-by":"crossref","unstructured":"Abualigah L, Diabat A, Sumari P, Gandomi AH (2021) A Novel Evolutionary Arithmetic Optimization Algorithm for Multilevel Thresholding Segmentation of COVID-19 CT Images","DOI":"10.3390\/pr9071155"},{"issue":"5","key":"5073_CR96","doi-asserted-by":"publisher","first-page":"1123","DOI":"10.1007\/s00521-015-2114-6","volume":"28","author":"VK Kamboj","year":"2017","unstructured":"Kamboj VK, Bath SK, Dhillon JS (2017) Hybrid HS\u2013random search algorithm considering ensemble and pitch violation for unit commitment problem. Neural Comput Appl 28(5):1123\u20131148. https:\/\/doi.org\/10.1007\/s00521-015-2114-6","journal-title":"Neural Comput Appl"},{"key":"5073_CR97","doi-asserted-by":"publisher","first-page":"043705","DOI":"10.1063\/1.5009247","volume":"10","author":"S Maghsudlu","year":"2018","unstructured":"Maghsudlu S, Mohammadi S (2018) Optimal scheduled unit commitment considering suitable power of electric vehicle and photovoltaic uncertainty. J Renew Sustain Ener 10:043705. https:\/\/doi.org\/10.1063\/1.5009247","journal-title":"J Renew Sustain Ener"},{"key":"5073_CR98","unstructured":"Jian X, Yong-Quan Z, Huan C (2013) A bat algorithm based on l\u00e9vy flights trajectory.\u00a0Pattern Recognit Artif Intell 26(9):829-837. http:\/\/manu46.magtech.com.cn\/Jweb_prai\/EN\/"},{"issue":"4","key":"5073_CR99","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(4):1053\u20131073. https:\/\/doi.org\/10.1007\/s00521-015-1920-1","journal-title":"Neural Comput Appl"},{"key":"5073_CR100","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":"5073_CR101","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/ISCBI.2015.8","volume":"2015","author":"GG Wang","year":"2016","unstructured":"Wang GG, Deb S, Coelho LDS (2016) Elephant Herding Optimization. Proc - 2015 3rd Int Symp Comput Bus Intell ISCBI 2015:1\u20135. https:\/\/doi.org\/10.1109\/ISCBI.2015.8","journal-title":"Proc - 2015 3rd Int Symp Comput Bus Intell ISCBI"},{"issue":"5","key":"5073_CR102","doi-asserted-by":"publisher","first-page":"706","DOI":"10.1515\/mt-2022-0012","volume":"64","author":"AR Yildiz","year":"2022","unstructured":"Yildiz AR, Mehta P (2022) Manta ray foraging optimization algorithm and hybrid Taguchi salp swarm-Nelder-Mead algorithm for the structural design of engineering components. Mater Test 64(5):706\u2013713. https:\/\/doi.org\/10.1515\/mt-2022-0012","journal-title":"Mater Test"},{"key":"5073_CR103","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/access.2020.2982796","volume":"PP","author":"Y Wei","year":"2020","unstructured":"Wei Y et al (2020) Predicting Entrepreneurial Intention of Students: An Extreme Learning Machine with Gaussian Barebone Harris hawks Optimizer. IEEE Access PP:1\u20131. https:\/\/doi.org\/10.1109\/access.2020.2982796","journal-title":"IEEE Access"},{"issue":"1","key":"5073_CR104","doi-asserted-by":"publisher","first-page":"97","DOI":"10.1080\/09720502.2020.1721670","volume":"23","author":"R Hans","year":"2020","unstructured":"Hans R, Kaur H, Kaur N (2020) Opposition-based Harris hawks optimization algorithm for feature selection in breast mass classification. J Interdiscip Math 23(1):97\u2013106. https:\/\/doi.org\/10.1080\/09720502.2020.1721670","journal-title":"J Interdiscip Math"},{"issue":"16","key":"5073_CR105","doi-asserted-by":"publisher","first-page":"3590","DOI":"10.3390\/s19163590","volume":"19","author":"DT Bui","year":"2019","unstructured":"Bui DT et al (2019) A Novel Swarm Intelligence -Harris hawks. Sensors 19(16):3590. https:\/\/doi.org\/10.3390\/s19163590","journal-title":"Sensors"},{"key":"5073_CR106","doi-asserted-by":"publisher","first-page":"3504642","DOI":"10.1155\/2020\/3504642","volume":"2020","author":"I Attiya","year":"2020","unstructured":"Attiya I, Abd Elaziz M, Xiong S (2020) Job scheduling in cloud computing using a modified harris hawks optimization and simulated annealing algorithm. Comput Intell Neurosci 2020:3504642. https:\/\/doi.org\/10.1155\/2020\/3504642","journal-title":"Comput Intell Neurosci"},{"key":"5073_CR107","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, Asghar A, Chen H, Wang M, Pan Z, Gandomi AH (2020) Multi-population differential evolution-assisted Harris hawks optimization\u202f: 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":"5073_CR108","doi-asserted-by":"publisher","first-page":"12","DOI":"10.3390\/rs11121421","volume":"11","author":"H Jia","year":"2019","unstructured":"Jia H, Lang C, Oliva D, Song W, Peng X (2019) Dynamic Harris hawks optimization with mutation mechanism for satellite image segmentation. Remote Sens 11:12. https:\/\/doi.org\/10.3390\/rs11121421","journal-title":"Remote Sens"},{"issue":"8","key":"5073_CR109","doi-asserted-by":"publisher","first-page":"735","DOI":"10.3139\/120.111378","volume":"61","author":"AR Y\u0131ld\u0131z","year":"2019","unstructured":"Y\u0131ld\u0131z AR, Y\u0131ld\u0131z BS, Sait SM, Bureerat S, Pholdee N (2019) A new hybrid Harris hawks-Nelder-Mead optimization algorithm for solving design and manufacturing problems. Mater Test 61(8):735\u2013743. https:\/\/doi.org\/10.3139\/120.111378","journal-title":"Mater Test"},{"key":"5073_CR110","doi-asserted-by":"publisher","first-page":"4","DOI":"10.3390\/app10041403","volume":"10","author":"Z Yu","year":"2020","unstructured":"Yu Z, Shi X, Zhou J, Chen X, Qiu X (2020) Effective assessment of blast-induced ground vibration using an optimized random forest model based on a harris hawks optimization algorithm. Appl Sci 10:4. https:\/\/doi.org\/10.3390\/app10041403","journal-title":"Appl Sci"},{"key":"5073_CR111","doi-asserted-by":"publisher","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 (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":"5073_CR112","doi-asserted-by":"publisher","unstructured":"Houssein E, Hosney M, Elhoseny M, Oliva D, Makram Mohamed W, Hassaballah M (2020) Hybrid Harris hawks optimization with cuckoo search for drug design and discovery in chemoinformatics. Sci Rep 10. https:\/\/doi.org\/10.1038\/s41598-020-71502-z","DOI":"10.1038\/s41598-020-71502-z"},{"key":"5073_CR113","doi-asserted-by":"publisher","unstructured":"Zhao J, Gao Z, Sun W (2020) The improved slime mould algorithm with Levy flight. https:\/\/doi.org\/10.1088\/1742-6596\/1617\/1\/012033","DOI":"10.1088\/1742-6596\/1617\/1\/012033"},{"key":"5073_CR114","doi-asserted-by":"publisher","first-page":"10","DOI":"10.3390\/w12102692","volume":"12","author":"SL Zubaidi","year":"2020","unstructured":"Zubaidi SL et al (2020) Hybridised artificial neural network model with slime mould algorithm: A novel methodology for prediction of urban stochastic water demand. Water (Switzerland) 12:10. https:\/\/doi.org\/10.3390\/w12102692","journal-title":"Water (Switzerland)"},{"key":"5073_CR115","doi-asserted-by":"publisher","first-page":"165277","DOI":"10.1016\/j.ijleo.2020.165277","volume":"223","author":"C Kumar","year":"2020","unstructured":"Kumar C, Raj TD, Premkumar M, Raj TD (2020) A new stochastic slime mould optimization algorithm for the estimation of solar photovoltaic cell parameters. Optik (Stuttg). 223:165277. https:\/\/doi.org\/10.1016\/j.ijleo.2020.165277","journal-title":"Optik (Stuttg)."},{"key":"5073_CR116","doi-asserted-by":"publisher","first-page":"106642","DOI":"10.1016\/j.asoc.2020.106642","volume":"95","author":"M Abdel-Basset","year":"2020","unstructured":"Abdel-Basset M, Chang V, Mohamed R (2020) HSMA_WOA: a hybrid novel Slime mould algorithm with whale optimization algorithm for tackling the image segmentation problem of chest X-ray images. Appl Soft Comput 95:106642. https:\/\/doi.org\/10.1016\/j.asoc.2020.106642","journal-title":"Appl Soft Comput"},{"key":"5073_CR117","doi-asserted-by":"publisher","first-page":"012083","DOI":"10.1088\/1742-6596\/1631\/1\/012083","volume":"1631","author":"Z-M Gao","year":"2020","unstructured":"Gao Z-M, Zhao J, Li S-R (2020) The Improved Slime Mould Algorithm with Cosine Controlling Parameters. J Phys Conf Ser 1631:012083. https:\/\/doi.org\/10.1088\/1742-6596\/1631\/1\/012083","journal-title":"J Phys Conf Ser"},{"key":"5073_CR118","doi-asserted-by":"publisher","first-page":"012071","DOI":"10.1088\/1742-6596\/1631\/1\/012071","volume":"1631","author":"J Zhao","year":"2020","unstructured":"Zhao J, Gao Z-M (2020) The chaotic slime mould algorithm with chebyshev map. J Phys Conf Ser 1631:012071. https:\/\/doi.org\/10.1088\/1742-6596\/1631\/1\/012071","journal-title":"J Phys Conf Ser"},{"key":"5073_CR119","doi-asserted-by":"publisher","first-page":"012034","DOI":"10.1088\/1742-6596\/1617\/1\/012034","volume":"1617","author":"Z-M Gao","year":"2020","unstructured":"Gao Z-M, Zhao J, Yang Y, Tian X-J (2020) The hybrid grey wolf optimization-slime mould algorithm. J Phys Conf Ser\u00a0 1617:012034. https:\/\/doi.org\/10.1088\/1742-6596\/1617\/1\/012034","journal-title":"J Phys Conf Ser\u00a0"},{"key":"5073_CR120","doi-asserted-by":"publisher","first-page":"18","DOI":"10.3390\/APP10186180","volume":"10","author":"M Liu","year":"2020","unstructured":"Liu M et al (2020) \u201cA two-way parallel slime mold algorithm by flow and distance for the travelling salesman problem. Appl Sci 10:18. https:\/\/doi.org\/10.3390\/APP10186180","journal-title":"Appl Sci"},{"issue":"8","key":"5073_CR121","doi-asserted-by":"publisher","first-page":"541","DOI":"10.1080\/02726343.2020.1838044","volume":"40","author":"A Durmus","year":"2020","unstructured":"Durmus A (2020) The optimal synthesis of thinned concentric circular antenna arrays using slime mold algorithm. Electromagnetics 40(8):541\u2013553. https:\/\/doi.org\/10.1080\/02726343.2020.1838044","journal-title":"Electromagnetics"},{"issue":"1","key":"5073_CR122","doi-asserted-by":"publisher","first-page":"67","DOI":"10.1145\/1389095.1389254","volume":"1","author":"DH Wolpert","year":"1997","unstructured":"Wolpert DH, Macready WG (1997) No Free Lunch Theorems for Optimization 1 Introduction. IEEE Trans Evol Comput 1(1):67\u201382. https:\/\/doi.org\/10.1145\/1389095.1389254","journal-title":"IEEE Trans Evol Comput"},{"key":"5073_CR123","doi-asserted-by":"publisher","first-page":"113974","DOI":"10.1016\/j.eswa.2020.113974","volume":"164","author":"W Zhou","year":"2020","unstructured":"Zhou W, Wang P, Heidari AA, Wang M, Chen H (2020) Multi-core Sine Cosine Optimization: Methods and Inclusive Analysis. Expert Syst Appl 164:113974. https:\/\/doi.org\/10.1016\/j.eswa.2020.113974","journal-title":"Expert Syst Appl"},{"issue":"2","key":"5073_CR124","doi-asserted-by":"publisher","first-page":"116","DOI":"10.1002\/j.1537-2197.1931.tb09577.x","volume":"18","author":"FL Howard","year":"1931","unstructured":"Howard FL (1931) the Life History of Physarum Polycephalum. Am J Bot 18(2):116\u2013133. https:\/\/doi.org\/10.1002\/j.1537-2197.1931.tb09577.x","journal-title":"Am J Bot"},{"key":"5073_CR125","doi-asserted-by":"publisher","first-page":"300","DOI":"10.1016\/j.future.2020.03.055","volume":"111","author":"S Li","year":"2020","unstructured":"Li S, Chen H, Wang M, Heidari AA, Mirjalili S (2020) Slime mould algorithm: A new method for stochastic optimization. Futur Gener Comput Syst 111:300\u2013323. https:\/\/doi.org\/10.1016\/j.future.2020.03.055","journal-title":"Futur Gener Comput Syst"},{"key":"5073_CR126","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. Future Gener Comput Syst 97:849\u2013872. https:\/\/doi.org\/10.1016\/j.future.2019.02.028","journal-title":"Future Gener Comput Syst"},{"issue":"4","key":"5073_CR127","doi-asserted-by":"publisher","first-page":"481","DOI":"10.1080\/00207160108805080","volume":"77","author":"JG Digalakis","year":"2001","unstructured":"Digalakis JG, Margaritis KG (2001) On benchmarking functions for genetic algorithms. Int J Comput Math 77(4):481\u2013506. https:\/\/doi.org\/10.1080\/00207160108805080","journal-title":"Int J Comput Math"},{"key":"5073_CR128","doi-asserted-by":"publisher","first-page":"66","DOI":"10.1016\/j.advengsoft.2014.08.003","volume":"77","author":"A Kaveh","year":"2014","unstructured":"Kaveh A, IlchiGhazaan M (2014) Enhanced colliding bodies optimization for design problems with continuous and discrete variables. Adv Eng Softw 77:66\u201375. https:\/\/doi.org\/10.1016\/j.advengsoft.2014.08.003","journal-title":"Adv Eng Softw"},{"key":"5073_CR129","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1002\/ett.4739","volume":"September 2022","author":"PG Dhawale","year":"2023","unstructured":"Dhawale PG, Kamboj VK, Bath SK (2023) A levy flight based strategy to improve the exploitation capability of arithmetic optimization algorithm for engineering global optimization problems. Trans Emerg Telecommun Technol September 2022:1\u201365. https:\/\/doi.org\/10.1002\/ett.4739","journal-title":"Trans Emerg Telecommun Technol"},{"issue":"4","key":"5073_CR130","doi-asserted-by":"publisher","first-page":"1149","DOI":"10.1007\/s40998-022-00524-2","volume":"46","author":"P Anand","year":"2022","unstructured":"Anand P, Rizwan M, Kaur S, Gulnar B, Vikram P, Kamboj K (2022) Optimal Sizing of Hybrid Renewable Energy System for Electricity Production for Remote Areas. Iran J Sci Technol Trans Electr Eng 46(4):1149\u20131174. https:\/\/doi.org\/10.1007\/s40998-022-00524-2","journal-title":"Iran J Sci Technol Trans Electr Eng"},{"issue":"2","key":"5073_CR131","doi-asserted-by":"publisher","first-page":"101548","DOI":"10.1016\/j.asej.2021.06.032","volume":"13","author":"A Fathy","year":"2021","unstructured":"Fathy A, Alharbi AG, Alshammari S, Hasanien HM (2021) Archimedes optimization algorithm based maximum power point tracker for wind energy generation system. Ain Shams Eng J 13(2):101548. https:\/\/doi.org\/10.1016\/j.asej.2021.06.032","journal-title":"Ain Shams Eng J"},{"issue":"2","key":"5073_CR132","doi-asserted-by":"publisher","first-page":"1183","DOI":"10.1007\/s00366-021-01487-4","volume":"39","author":"D Dhawale","year":"2023","unstructured":"Dhawale D, Kamboj VK, Anand P (2023) An improved Chaotic Harris Hawks Optimizer for solving numerical and engineering optimization problems. Eng Comput 39(2):1183\u20131228. https:\/\/doi.org\/10.1007\/s00366-021-01487-4","journal-title":"Eng Comput"},{"issue":"7\u20138","key":"5073_CR133","doi-asserted-by":"publisher","first-page":"1569","DOI":"10.1007\/s00521-014-1640-y","volume":"25","author":"S Mirjalili","year":"2014","unstructured":"Mirjalili S, Lewis A (2014) Adaptive gbest-guided gravitational search algorithm. Neural Comput Appl 25(7\u20138):1569\u20131584. https:\/\/doi.org\/10.1007\/s00521-014-1640-y","journal-title":"Neural Comput Appl"},{"key":"5073_CR134","doi-asserted-by":"publisher","unstructured":"Mirjalili S, Mirjalili S, Hatamlou A (2015) Multi-verse optimizer: a nature-inspired algorithm for global optimization. Neural Comput Appl 27. https:\/\/doi.org\/10.1007\/s00521-015-1870-7","DOI":"10.1007\/s00521-015-1870-7"},{"key":"5073_CR135","doi-asserted-by":"publisher","unstructured":"Nakamura R, Pereira L, Costa K, Rodrigues D, Papa J, Yang X-S (2012) BBA: a binary bat algorithm for feature selection. In: Brazilian symposium of computer graphic and image processing. https:\/\/doi.org\/10.1109\/SIBGRAPI.2012.47","DOI":"10.1109\/SIBGRAPI.2012.47"},{"key":"5073_CR136","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1088\/1742-6596\/1631\/1\/012071","volume":"1631","author":"J Zhao","year":"2020","unstructured":"Zhao J, Gao ZM (2020) The Chaotic Slime Mould Algorithm with Chebyshev Map. J Phys Conf Ser 1631:1. https:\/\/doi.org\/10.1088\/1742-6596\/1631\/1\/012071","journal-title":"J Phys Conf Ser"},{"key":"5073_CR137","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":"5073_CR138","doi-asserted-by":"publisher","first-page":"106018","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"},{"issue":"5","key":"5073_CR139","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\u202f: A new population based algorithm for solving constrained engineering optimization problems. Appl Soft Comput J 13(5):2592\u20132612. https:\/\/doi.org\/10.1016\/j.asoc.2012.11.026","journal-title":"Appl Soft Comput J"},{"issue":"11","key":"5073_CR140","doi-asserted-by":"publisher","first-page":"1650138","DOI":"10.1142\/S0218126616501383","volume":"25","author":"K Shankar","year":"2016","unstructured":"Shankar K, Eswaran P (2016) \u201cRGB-Based Secure Share Creation in Visual Cryptography Using Optimal Elliptic Curve Cryptography Technique. J Circuits Syst Comput 25(11):1650138. https:\/\/doi.org\/10.1142\/S0218126616501383","journal-title":"J Circuits Syst Comput"},{"issue":"1","key":"5073_CR141","doi-asserted-by":"publisher","first-page":"181","DOI":"10.1109\/TSTE.2015.2482120","volume":"7","author":"S Mohanty","year":"2016","unstructured":"Mohanty S, Subudhi B, Ray PK (2016) A new MPPT design using grey wolf optimization technique for photovoltaic system under partial shading conditions. IEEE Trans Sustain Energy 7(1):181\u2013188. https:\/\/doi.org\/10.1109\/TSTE.2015.2482120","journal-title":"IEEE Trans Sustain Energy"},{"key":"5073_CR142","doi-asserted-by":"publisher","first-page":"484","DOI":"10.1016\/j.eswa.2017.07.043","volume":"90","author":"M AbdElaziz","year":"2017","unstructured":"AbdElaziz M, Oliva D, Xiong S (2017) An improved opposition-based sine cosine algorithm for global optimization. Expert Syst Appl 90:484\u2013500. https:\/\/doi.org\/10.1016\/j.eswa.2017.07.043","journal-title":"Expert Syst Appl"},{"key":"5073_CR143","doi-asserted-by":"publisher","DOI":"10.1115\/1.2919393","author":"BK Kannan","year":"1994","unstructured":"Kannan BK, Kramer SN (1994) An augmented lagrange multiplier based method for mixed integer discrete continuous optimization and its applications to mechanical design. J Mech Des Trans ASME. https:\/\/doi.org\/10.1115\/1.2919393","journal-title":"J Mech Des Trans ASME"},{"key":"5073_CR144","doi-asserted-by":"publisher","unstructured":"Hameed IA, Bye RT, Osen OL (2016) Grey wolf optimizer (GWO) for automated offshore crane design. 2016 IEEE Symposium Series on Computational Intelligence (SSCI), pp 1\u20136. https:\/\/doi.org\/10.1109\/SSCI.2016.7849998","DOI":"10.1109\/SSCI.2016.7849998"},{"key":"5073_CR145","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":"5073_CR146","doi-asserted-by":"publisher","first-page":"139","DOI":"10.1016\/j.ijepes.2012.11.024","volume":"48","author":"P Karthikeyan","year":"2013","unstructured":"Karthikeyan P, Raglend J, Kothari DP (2013) A review on market power in deregulated electricity market. Int J Electr Power Energy Syst 48:139\u2013147. https:\/\/doi.org\/10.1016\/j.ijepes.2012.11.024","journal-title":"Int J Electr Power Energy Syst"},{"key":"5073_CR147","first-page":"319","volume":"32","author":"LC Cagnina","year":"2008","unstructured":"Cagnina LC, Esquivel SC, Nacional U, Luis DS, Luis S, Coello CAC (2008) Solving Engineering Optimization Problems with the Simple Constrained Particle Swarm Optimizer 1 Introduction 2 Literature review 3 Our proposed approach. SiC-PSO 32:319\u2013326","journal-title":"SiC-PSO"},{"issue":"4","key":"5073_CR148","doi-asserted-by":"publisher","first-page":"1373","DOI":"10.1109\/59.41687","volume":"4","author":"S Virmani","year":"1989","unstructured":"Virmani S, Adrian EC, Imhof K, Mukherjee S (1989) Implementation of a Lagrangian relaxation based unit commitment problem. IEEE Trans Power Syst 4(4):1373\u20131380. https:\/\/doi.org\/10.1109\/59.41687","journal-title":"IEEE Trans Power Syst"},{"issue":"2","key":"5073_CR149","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(2):444\u2013451","journal-title":"IEEE Trans Power Appar Syst"},{"key":"5073_CR150","doi-asserted-by":"publisher","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. https:\/\/doi.org\/10.1016\/j.advengsoft.2017.05.014","journal-title":"Adv Eng Softw"},{"key":"5073_CR151","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 \u2013 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":"5073_CR152","doi-asserted-by":"publisher","first-page":"105277","DOI":"10.1016\/j.knosys.2019.105277","volume":"191","author":"D Pelusi","year":"2020","unstructured":"Pelusi D, Mascella R, Tallini L, Nayak J, Naik B, Deng Y (2020) An Improved Moth-Flame Optimization algorithm with hybrid search phase. Knowledge-Based Syst. 191:105277. https:\/\/doi.org\/10.1016\/j.knosys.2019.105277","journal-title":"Knowledge-Based Syst."},{"key":"5073_CR153","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-10-5221-7_14","author":"B Zolghadr-Asli","year":"2018","unstructured":"Zolghadr-Asli B, Bozorg-Haddad O, Chu X (2018) \u201cCrow search algorithm (CSA)\u201d, Studies in Computational. Intelligence. https:\/\/doi.org\/10.1007\/978-981-10-5221-7_14","journal-title":"Intelligence"},{"issue":"4","key":"5073_CR154","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(4):1168\u20131183. https:\/\/doi.org\/10.1016\/j.isatra.2014.03.018","journal-title":"ISA Trans"},{"issue":"1-3","key":"5073_CR155","doi-asserted-by":"publisher","first-page":"337","DOI":"10.1080\/03052159908941377","volume":"31","author":"CA Coello","year":"1999","unstructured":"Coello CA, Christiansen AD (1999) Moses: A multiobjective optimization tool for engineering design. Eng Optim 31(1\u20133):337\u2013368. https:\/\/doi.org\/10.1080\/03052159908941377","journal-title":"Eng Optim"},{"key":"5073_CR156","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":"0","key":"5073_CR157","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1080\/0305215X.2019.1624740","volume":"0","author":"AG Hussien","year":"2019","unstructured":"Hussien AG, Hassanien AE, Houssein EH, Azar AT (2019) New binary whale optimization algorithm for discrete optimization problems. Eng Optim 0(0):1\u201315. https:\/\/doi.org\/10.1080\/0305215X.2019.1624740","journal-title":"Eng Optim"}],"container-title":["Applied Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-023-05073-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10489-023-05073-7\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-023-05073-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,2,16]],"date-time":"2024-02-16T12:34:02Z","timestamp":1708086842000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10489-023-05073-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,1]]},"references-count":157,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2024,1]]}},"alternative-id":["5073"],"URL":"https:\/\/doi.org\/10.1007\/s10489-023-05073-7","relation":{},"ISSN":["0924-669X","1573-7497"],"issn-type":[{"value":"0924-669X","type":"print"},{"value":"1573-7497","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,1]]},"assertion":[{"value":"29 September 2023","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"27 January 2024","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}