{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,18]],"date-time":"2026-06-18T04:00:32Z","timestamp":1781755232486,"version":"3.54.5"},"reference-count":62,"publisher":"Springer Science and Business Media LLC","issue":"5","license":[{"start":{"date-parts":[[2021,11,17]],"date-time":"2021-11-17T00:00:00Z","timestamp":1637107200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,11,17]],"date-time":"2021-11-17T00:00:00Z","timestamp":1637107200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Artif Intell Rev"],"published-print":{"date-parts":[[2022,6]]},"DOI":"10.1007\/s10462-021-10100-5","type":"journal-article","created":{"date-parts":[[2021,11,17]],"date-time":"2021-11-17T11:03:16Z","timestamp":1637146996000},"page":"3979-4040","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":71,"title":["Chaotic slime mould optimization algorithm for global optimization"],"prefix":"10.1007","volume":"55","author":[{"given":"Osman","family":"Altay","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2021,11,17]]},"reference":[{"key":"10100_CR1","doi-asserted-by":"publisher","first-page":"43473","DOI":"10.1109\/ACCESS.2019.2907012","volume":"7","author":"JM Abdullah","year":"2019","unstructured":"Abdullah JM, Ahmed T (2019) Fitness-dependent optimizer: inspired by the bee swarming reproductive process. IEEE Access 7:43473\u201343486","journal-title":"IEEE Access"},{"issue":"2","key":"10100_CR2","doi-asserted-by":"publisher","first-page":"305","DOI":"10.1007\/s12065-018-0188-7","volume":"14","author":"A Agrawal","year":"2018","unstructured":"Agrawal A, Tripathi S (2018) Particle swarm optimization with adaptive inertia weight based on cumulative binomial probability. Evol Intel 14(2):305\u2013313","journal-title":"Evol Intel"},{"key":"10100_CR3","doi-asserted-by":"publisher","first-page":"163","DOI":"10.1007\/978-981-13-0341-8_15","volume":"759","author":"EV Altay","year":"2019","unstructured":"Altay EV, Alatas B (2019) Performance comparisons of socially inspired metaheuristic algorithms on unconstrained global optimization. Adv Intell Syst Comput 759:163\u2013175. https:\/\/doi.org\/10.1007\/978-981-13-0341-8_15","journal-title":"Adv Intell Syst Comput"},{"issue":"2","key":"10100_CR4","doi-asserted-by":"publisher","first-page":"1373","DOI":"10.1007\/s10462-019-09704-9","volume":"53","author":"EV Altay","year":"2020","unstructured":"Altay EV, Alatas B (2020) Bird swarm algorithms with chaotic mapping. Artif Intell Rev 53(2):1373\u20131414","journal-title":"Artif Intell Rev"},{"key":"10100_CR5","doi-asserted-by":"publisher","first-page":"198","DOI":"10.1016\/j.ins.2020.12.055","volume":"554","author":"EV Altay","year":"2021","unstructured":"Altay EV, Alatas B (2021) Differential evolution and sine cosine algorithm based novel hybrid multi-objective approaches for numerical association rule mining. Inf Sci 554:198\u2013221","journal-title":"Inf Sci"},{"issue":"8","key":"10100_CR6","doi-asserted-by":"publisher","first-page":"4385","DOI":"10.1007\/s00521-018-3343-2","volume":"31","author":"S Arora","year":"2019","unstructured":"Arora S, Anand P (2019) Chaotic grasshopper optimization algorithm for global optimization. Neural Comput Appl 31(8):4385\u20134405. https:\/\/doi.org\/10.1007\/s00521-018-3343-2","journal-title":"Neural Comput Appl"},{"key":"10100_CR7","unstructured":"Awad N, Ali M, Liang J, Qu B, Suganthan P (2016) Problem definitions and evaluation criteria for the CEC 2017 special session and competition on single objective real-parameter numerical optimization. Technical Report"},{"key":"10100_CR8","doi-asserted-by":"crossref","unstructured":"Becker M (2015) On the efficiency of nature-inspired algorithms for generation of fault-tolerant graphs. In: Conference on systems, man, and cybernetics, IEEE pp 1657\u20131663. https:\/\/ieeexplore.ieee.org\/abstract\/document\/7379424\/","DOI":"10.1109\/SMC.2015.292"},{"issue":"4","key":"10100_CR9","doi-asserted-by":"publisher","first-page":"1821","DOI":"10.1007\/S00158-020-02578-4","volume":"62","author":"A Bigham","year":"2020","unstructured":"Bigham A, Gholizadeh S (2020) Topology optimization of nonlinear single-layer domes by an improved electro-search algorithm and its performance analysis using statistical tests. Struct Multidiscip Optim 62(4):1821\u20131848. https:\/\/doi.org\/10.1007\/S00158-020-02578-4","journal-title":"Struct Multidiscip Optim"},{"key":"10100_CR10","doi-asserted-by":"publisher","first-page":"110434","DOI":"10.1016\/j.chaos.2020.110434","volume":"141","author":"H Bingol","year":"2020","unstructured":"Bingol H, Alatas B (2020) Chaos based optics inspired optimization algorithms as global solution search approach. Chaos Solitons Fractals 141:110434","journal-title":"Chaos Solitons Fractals"},{"key":"10100_CR11","doi-asserted-by":"publisher","first-page":"22","DOI":"10.1016\/j.simpat.2017.04.001","volume":"76","author":"JM Czerniak","year":"2017","unstructured":"Czerniak JM, Zarzycki H, Ewald D (2017) AAO as a new strategy in modeling and simulation of constructional problems optimization. Simul Model Pract Theory 76:22\u201333","journal-title":"Simul Model Pract Theory"},{"issue":"1","key":"10100_CR12","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1016\/j.swevo.2011.02.002","volume":"1","author":"J Derrac","year":"2011","unstructured":"Derrac J, Garc\u00eda S, Molina D, Herrera F (2011) A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithms. Swarm Evol Comput 1(1):3\u201318. https:\/\/doi.org\/10.1016\/j.swevo.2011.02.002","journal-title":"Swarm Evol Comput"},{"key":"10100_CR13","doi-asserted-by":"publisher","DOI":"10.1007\/S00366-021-01409-4","author":"D Dhawale","year":"2021","unstructured":"Dhawale D, Kamboj VK, Anand P (2021) An effective solution to numerical and multi-disciplinary design optimization problems using chaotic slime mold algorithm. Eng Comput. https:\/\/doi.org\/10.1007\/S00366-021-01409-4","journal-title":"Eng Comput"},{"key":"10100_CR14","doi-asserted-by":"crossref","unstructured":"Ekinci S, Izci D, Zeynelgil HL, Orenc S (2020) An application of slime mould algorithm for optimizing parameters of power system stabilizer. In: International symposium on multidisciplinary studies and \u0131nnovative technologies (ISMSIT), IEEE, pp. 1\u20135. https:\/\/ieeexplore.ieee.org\/abstract\/document\/9254597\/","DOI":"10.1109\/ISMSIT50672.2020.9254597"},{"issue":"6","key":"10100_CR15","doi-asserted-by":"publisher","first-page":"915","DOI":"10.1080\/0305215X.2016.1218003","volume":"49","author":"F Erdal","year":"2017","unstructured":"Erdal F (2017) A firefly algorithm for optimum design of new-generation beams. Eng Optim 49(6):915\u2013931","journal-title":"Eng Optim"},{"key":"10100_CR16","doi-asserted-by":"publisher","first-page":"156","DOI":"10.1016\/j.eswa.2018.06.023","volume":"112","author":"AA Ewees","year":"2018","unstructured":"Ewees AA, Abd Elaziz M, Houssein EH (2018) Improved grasshopper optimization algorithm using opposition-based learning. Expert Syst Appl 112:156\u2013172","journal-title":"Expert Syst Appl"},{"issue":"1","key":"10100_CR17","doi-asserted-by":"publisher","first-page":"012083","DOI":"10.1088\/1742-6596\/1631\/1\/012083","volume":"1631","author":"ZM Gao","year":"2020","unstructured":"Gao ZM, Zhao J, Li SR (2020) The \u0131mproved slime mould algorithm with cosine controlling parameters. J Phys Conf Ser 1631(1):012083. https:\/\/doi.org\/10.1088\/1742-6596\/1631\/1\/012083","journal-title":"J Phys Conf Ser"},{"key":"10100_CR18","doi-asserted-by":"publisher","first-page":"106250","DOI":"10.1016\/j.compstruc.2020.106250","volume":"234","author":"S Gholizadeh","year":"2020","unstructured":"Gholizadeh S, Danesh M, Gheyratmand C (2020) A new Newton metaheuristic algorithm for discrete performance-based design optimization of steel moment frames. Comput Struct 234:106250","journal-title":"Comput Struct"},{"issue":"4","key":"10100_CR19","doi-asserted-by":"publisher","first-page":"1045","DOI":"10.1007\/s00366-017-0515-0","volume":"33","author":"S Gholizadeh","year":"2017","unstructured":"Gholizadeh S, Baghchevan A (2017) Multi-objective seismic design optimization of steel frames by a chaotic meta-heuristic algorithm. Eng Comput 33(4):1045\u20131060","journal-title":"Eng Comput"},{"issue":"11","key":"10100_CR20","doi-asserted-by":"publisher","first-page":"1829","DOI":"10.1080\/0305215X.2017.1417402","volume":"50","author":"S Gholizadeh","year":"2018","unstructured":"Gholizadeh S, Milany A (2018) An improved fireworks algorithm for discrete sizing optimization of steel skeletal structures. Eng Optim 50(11):1829\u20131849. https:\/\/doi.org\/10.1080\/0305215X.2017.1417402","journal-title":"Eng Optim"},{"issue":"14","key":"10100_CR21","doi-asserted-by":"publisher","first-page":"10759","DOI":"10.1007\/S00521-019-04611-0","volume":"32","author":"FA Hashim","year":"2020","unstructured":"Hashim FA, Houssein EH, Hussain K, Mabrouk MS, Al-Atabany W (2020) A modified Henry gas solubility optimization for solving motif discovery problem. Neural Comput Appl 32(14):10759\u201310771. https:\/\/doi.org\/10.1007\/S00521-019-04611-0","journal-title":"Neural Comput Appl"},{"issue":"3","key":"10100_CR22","doi-asserted-by":"publisher","first-page":"1531","DOI":"10.1007\/s10489-020-01893-z","volume":"51","author":"FA Hashim","year":"2021","unstructured":"Hashim FA, Hussain K, Houssein EH, Mabrouk MS, Al-Atabany W (2021) Archimedes optimization algorithm: a new metaheuristic algorithm for solving optimization problems. Appl Intell 51(3):1531\u20131551","journal-title":"Appl Intell"},{"key":"10100_CR23","doi-asserted-by":"publisher","first-page":"104155","DOI":"10.1016\/j.engappai.2021.104155","volume":"100","author":"MH Hassan","year":"2021","unstructured":"Hassan MH, Houssein EH, Mahdy MA, Kamel S (2021) An improved manta ray foraging optimizer for cost-effective emission dispatch problems. Eng Appl Artif Intell 100:104155","journal-title":"Eng Appl Artif Intell"},{"key":"10100_CR24","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","journal-title":"Futur Gener Comput Syst"},{"issue":"1","key":"10100_CR25","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/s41598-020-71502-z","volume":"10","author":"EH Houssein","year":"2020","unstructured":"Houssein EH, Hosney ME, Elhoseny M, Oliva D, Mohamed WM, Hassaballah M (2020a) Hybrid Harris hawks optimization with cuckoo search for drug design and discovery in chemoinformatics. Sci Rep 10(1):1\u201322","journal-title":"Sci Rep"},{"key":"10100_CR27","doi-asserted-by":"publisher","first-page":"19381","DOI":"10.1109\/ACCESS.2020.2968981","volume":"8","author":"EH Houssein","year":"2020","unstructured":"Houssein EH, Saad MR, Hussain K, Zhu W, Shaban H, Hassaballah M (2020b) Optimal sink node placement in large scale wireless sensor networks based on Harris\u2019 hawk optimization algorithm. IEEE Access 8:19381\u201319397","journal-title":"IEEE Access"},{"key":"10100_CR28","doi-asserted-by":"publisher","first-page":"114689","DOI":"10.1016\/j.eswa.2021.114689","volume":"174","author":"EH Houssein","year":"2021","unstructured":"Houssein EH, Mahdy MA, Blondin MJ, Shebl D, Mohamed WM (2021a) Hybrid slime mould algorithm with adaptive guided differential evolution algorithm for combinatorial and global optimization problems. Expert Syst Appl 174:114689","journal-title":"Expert Syst Appl"},{"key":"10100_CR29","doi-asserted-by":"publisher","first-page":"147","DOI":"10.1016\/j.jare.2020.10.001","volume":"29","author":"EH Houssein","year":"2021","unstructured":"Houssein EH, Mahdy MA, Eldin MG, Shebl D, Mohamed WM, Abdel-Aty M (2021b) Optimizing quantum cloning circuit parameters based on adaptive guided differential evolution algorithm. J Adv Res 29:147\u2013157","journal-title":"J Adv Res"},{"key":"10100_CR30","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 18:116\u2013133","journal-title":"Am J Bot"},{"key":"10100_CR31","doi-asserted-by":"publisher","first-page":"114778","DOI":"10.1016\/j.eswa.2021.114778","volume":"176","author":"K Hussain","year":"2021","unstructured":"Hussain K, Neggaz N, Zhu W, Houssein EH (2021) An efficient hybrid sine-cosine Harris hawks optimization for low and high-dimensional feature selection. Expert Syst Appl 176:114778","journal-title":"Expert Syst Appl"},{"key":"10100_CR32","doi-asserted-by":"crossref","unstructured":"Izci D (2021) An enhanced slime mould algorithm for function optimization. In: 3rd International congress on human-computer \u0131nteraction, optimization and robotic applications (HORA), pp 1\u20135. IEEE. https:\/\/ieeexplore.ieee.org\/abstract\/document\/9461325\/","DOI":"10.1109\/HORA52670.2021.9461325"},{"issue":"1","key":"10100_CR33","doi-asserted-by":"publisher","first-page":"151","DOI":"10.5152\/electrica.2021.20077","volume":"21","author":"D \u0130zci","year":"2021","unstructured":"\u0130zci D, Ekinci S (2021) Comparative performance analysis of slime mould algorithm for efficient design of proportional\u2013integral\u2013derivative controller. Electrica 21(1):151\u2013159","journal-title":"Electrica"},{"issue":"15","key":"10100_CR34","doi-asserted-by":"publisher","first-page":"3175","DOI":"10.1016\/j.ins.2011.03.018","volume":"181","author":"D Jia","year":"2011","unstructured":"Jia D, Zheng G, Khan MK (2011) An effective memetic differential evolution algorithm based on chaotic local search. Inf Sci 181(15):3175\u20133187","journal-title":"Inf Sci"},{"issue":"3","key":"10100_CR35","first-page":"275","volume":"5","author":"G Kaur","year":"2018","unstructured":"Kaur G, Arora S (2018) Chaotic whale optimization algorithm. J Comput Des Eng 5(3):275\u2013284","journal-title":"J Comput Des Eng"},{"key":"10100_CR36","unstructured":"Kellert S (1994) In the wake of chaos: unpredictable order in dynamical systems. https:\/\/www.google.com\/books?hl=tr&lr=&id=KtkgeB7XOYwC&oi=fnd&pg=PR5&dq=Kellert,+S.+H.+(1994).+In+the+wake+of+chaos:+Unpredictable+order+in+dynamical+systems,+University+of+Chicago+Press&ots=iy2rwevgoS&sig=wX4KCY4AGJqfBu-zVOzaoCngAbg"},{"key":"10100_CR37","doi-asserted-by":"crossref","unstructured":"Kennedy J, Eberhart R (1995) Particle swarm optimization. In: Proceedings of ICNN\u201995-international conference on neural networks, vol 4, pp 1942\u20131948. IEEE","DOI":"10.1109\/ICNN.1995.488968"},{"issue":"4","key":"10100_CR38","first-page":"458","volume":"5","author":"M Kohli","year":"2018","unstructured":"Kohli M, Arora S (2018) Chaotic grey wolf optimization algorithm for constrained optimization problems. J Comput Des Eng 5(4):458\u2013472","journal-title":"J Comput Des Eng"},{"key":"10100_CR39","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","journal-title":"Futur Gener Comput Syst"},{"issue":"5","key":"10100_CR40","doi-asserted-by":"publisher","first-page":"1261","DOI":"10.1016\/j.chaos.2004.11.095","volume":"25","author":"B Liu","year":"2005","unstructured":"Liu B, Wang L, Jin YH, Tang F, Huang DX (2005) Improved particle swarm optimization combined with chaos. Chaos Solitons Fractals 25(5):1261\u20131271","journal-title":"Chaos Solitons Fractals"},{"issue":"2","key":"10100_CR41","doi-asserted-by":"publisher","first-page":"114","DOI":"10.1504\/IJBIC.2019.101639","volume":"14","author":"XB Meng","year":"2019","unstructured":"Meng XB, Li HX, Gao XZ (2019) An adaptive reinforcement learning-based bat algorithm for structural design problems. Int J Bio-Inspired Comput 14(2):114\u2013124","journal-title":"Int J Bio-Inspired Comput"},{"key":"10100_CR42","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","journal-title":"Adv Eng Softw"},{"key":"10100_CR43","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","journal-title":"Adv Eng Softw"},{"key":"10100_CR44","doi-asserted-by":"publisher","first-page":"446","DOI":"10.1016\/j.knosys.2015.08.010","volume":"89","author":"M Miti\u0107","year":"2015","unstructured":"Miti\u0107 M, Vukovi\u0107 N, Petrovi\u0107 M, Miljkovi\u0107 Z (2015) Chaotic fruit fly optimization algorithm. Knowl Based Syst 89:446\u2013458","journal-title":"Knowl Based Syst"},{"key":"10100_CR45","doi-asserted-by":"publisher","DOI":"10.1007\/S00500-021-06140-2","author":"MK Naik","year":"2021","unstructured":"Naik MK, Panda R, Abraham A (2021) Adaptive opposition slime mould algorithm. Soft Comput. https:\/\/doi.org\/10.1007\/S00500-021-06140-2","journal-title":"Soft Comput"},{"issue":"3","key":"10100_CR46","doi-asserted-by":"publisher","first-page":"195","DOI":"10.1016\/S0301-4622(00)00108-3","volume":"84","author":"T Nakagaki","year":"2000","unstructured":"Nakagaki T, Yamada H, Ueda T (2000) Interaction between cell shape and contraction pattern in the Physarum plasmodium. Biophys Chem 84(3):195\u2013204","journal-title":"Biophys Chem"},{"key":"10100_CR47","doi-asserted-by":"publisher","first-page":"115352","DOI":"10.1016\/j.eswa.2021.115352","volume":"183","author":"I Naruei","year":"2021","unstructured":"Naruei I, Keynia F (2021) A new optimization method based on COOT bird natural life model. Expert Syst Appl 183:115352","journal-title":"Expert Syst Appl"},{"issue":"6","key":"10100_CR48","doi-asserted-by":"publisher","first-page":"4632","DOI":"10.1016\/j.eswa.2009.12.045","volume":"37","author":"AB Ozer","year":"2010","unstructured":"Ozer AB (2010) CIDE: chaotically initialized differential evolution. Expert Syst Appl 37(6):4632\u20134641","journal-title":"Expert Syst Appl"},{"key":"10100_CR49","doi-asserted-by":"publisher","first-page":"290","DOI":"10.1016\/j.autcon.2017.10.019","volume":"85","author":"D Prayogo","year":"2018","unstructured":"Prayogo D, Cheng MY, Wu YW, Herdany AA, Prayogo H (2018) Differential Big Bang-Big Crunch algorithm for construction-engineering design optimization. Autom Constr 85:290\u2013304","journal-title":"Autom Constr"},{"key":"10100_CR50","doi-asserted-by":"crossref","unstructured":"Rizk-Allah RM, Hassanien AE, Song D (2021) Chaos-opposition-enhanced slime mould algorithm for minimizing the cost of energy for the wind turbines on high-altitude sites. ISA Trans. https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0019057821002081","DOI":"10.1016\/j.isatra.2021.04.011"},{"key":"10100_CR51","doi-asserted-by":"publisher","first-page":"73","DOI":"10.1016\/j.swevo.2016.03.002","volume":"29","author":"V \u0160e\u0161um-\u010cavi\u0107","year":"2016","unstructured":"\u0160e\u0161um-\u010cavi\u0107 V, K\u00fchn E, Kanev D (2016) Bio-inspired search algorithms for unstructured P2P overlay networks. Swarm Evol Comput 29:73\u201393","journal-title":"Swarm Evol Comput"},{"issue":"4","key":"10100_CR52","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","journal-title":"J Global Optim"},{"issue":"5","key":"10100_CR53","doi-asserted-by":"publisher","first-page":"883","DOI":"10.1080\/00207160.2018.1463438","volume":"96","author":"JH Tam","year":"2019","unstructured":"Tam JH, Ong ZC, Ismail Z, Ang BC, Khoo SY (2019) A new hybrid GA\u2212ACO\u2212PSO algorithm for solving various engineering design problems. Int J Comput Math 96(5):883\u2013919","journal-title":"Int J Comput Math"},{"key":"10100_CR54","doi-asserted-by":"crossref","unstructured":"T\u00f6rn A, \u017dilinskas A (1989) Global optimization. https:\/\/link.springer.com\/978-3-540-50871-7","DOI":"10.1007\/3-540-50871-6"},{"issue":"3","key":"10100_CR55","doi-asserted-by":"publisher","first-page":"531","DOI":"10.1007\/s12530-018-9250-z","volume":"11","author":"A Tzanetos","year":"2020","unstructured":"Tzanetos A, Dounias G (2020) Sonar inspired optimization (SIO) in engineering applications. Evol Syst 11(3):531\u2013539. https:\/\/doi.org\/10.1007\/s12530-018-9250-z","journal-title":"Evol Syst"},{"key":"10100_CR56","doi-asserted-by":"publisher","first-page":"17","DOI":"10.1016\/j.ins.2014.02.123","volume":"274","author":"GG Wang","year":"2014","unstructured":"Wang GG, Guo L, Gandomi AH, Hao GS, Wang H (2014) Chaotic krill herd algorithm. Inf Sci 274:17\u201334","journal-title":"Inf Sci"},{"key":"10100_CR57","doi-asserted-by":"publisher","first-page":"708","DOI":"10.1016\/j.ast.2018.04.047","volume":"78","author":"X Wang","year":"2018","unstructured":"Wang X, Deng Y, Duan H (2018) Edge-based target detection for unmanned aerial vehicles using competitive bird swarm algorithm. Aerosp Sci Technol 78:708\u2013720","journal-title":"Aerosp Sci Technol"},{"key":"10100_CR58","first-page":"171","volume-title":"Critical values and probability levels for the Wilcoxon rank sum test and the Wilcoxon signed rank test","author":"F Wilcoxon","year":"1963","unstructured":"Wilcoxon F, Katti SK, Wilcox RA (1963) Critical values and probability levels for the Wilcoxon rank sum test and the Wilcoxon signed rank test. American Cyanamid, Pearl River, pp 171\u2013176"},{"issue":"8","key":"10100_CR59","doi-asserted-by":"publisher","first-page":"11472","DOI":"10.4249\/scholarpedia.11472","volume":"6","author":"XS Yang","year":"2011","unstructured":"Yang XS (2011) Metaheuristic optimization. Scholarpedia 6(8):11472","journal-title":"Scholarpedia"},{"issue":"2","key":"10100_CR60","doi-asserted-by":"publisher","first-page":"168","DOI":"10.1088\/0253-6102\/38\/2\/168","volume":"38","author":"LJ Yang","year":"2002","unstructured":"Yang LJ, Chen TL (2002) Application of chaos in genetic algorithms. Commun Theor Phys 38(2):168\u2013172. https:\/\/doi.org\/10.1088\/0253-6102\/38\/2\/168","journal-title":"Commun Theor Phys"},{"key":"10100_CR61","unstructured":"Yu KD, Haeusler MH, Fabbri A, Simons K (2018) Bicycle pathway generation through a weighted digital slime mold algorithm via topographical analysis. http:\/\/papers.cumincad.org\/cgi-bin\/works\/paper\/caadria2018_188"},{"issue":"1","key":"10100_CR62","doi-asserted-by":"publisher","first-page":"012033","DOI":"10.1088\/1742-6596\/1617\/1\/012033","volume":"1617","author":"J Zhao","year":"2020","unstructured":"Zhao J, Gao ZM, Sun W (2020) The improved slime mould algorithm with Levy flight. J Phys Conf Ser 1617(1):012033. https:\/\/doi.org\/10.1088\/1742-6596\/1617\/1\/012033","journal-title":"J Phys Conf Ser"},{"issue":"1","key":"10100_CR63","doi-asserted-by":"publisher","first-page":"012029","DOI":"10.1088\/1742-6596\/1682\/1\/012029","volume":"1682","author":"J Zhao","year":"2020","unstructured":"Zhao J, Gao ZM (2020) The hybridized Harris hawk optimization and slime mould algorithm. J Phys Conf Ser 1682(1):012029. https:\/\/doi.org\/10.1088\/1742-6596\/1682\/1\/012029","journal-title":"J Phys Conf Ser"}],"container-title":["Artificial Intelligence Review"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10462-021-10100-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10462-021-10100-5\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10462-021-10100-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,12]],"date-time":"2024-09-12T11:14:40Z","timestamp":1726139680000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10462-021-10100-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,11,17]]},"references-count":62,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2022,6]]}},"alternative-id":["10100"],"URL":"https:\/\/doi.org\/10.1007\/s10462-021-10100-5","relation":{},"ISSN":["0269-2821","1573-7462"],"issn-type":[{"value":"0269-2821","type":"print"},{"value":"1573-7462","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,11,17]]},"assertion":[{"value":"17 November 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}