{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,20]],"date-time":"2026-03-20T00:55:56Z","timestamp":1773968156357,"version":"3.50.1"},"reference-count":62,"publisher":"Springer Science and Business Media LLC","issue":"33","license":[{"start":{"date-parts":[[2024,8,23]],"date-time":"2024-08-23T00:00:00Z","timestamp":1724371200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,8,23]],"date-time":"2024-08-23T00:00:00Z","timestamp":1724371200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["12102146"],"award-info":[{"award-number":["12102146"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput & Applic"],"published-print":{"date-parts":[[2024,11]]},"DOI":"10.1007\/s00521-024-10327-7","type":"journal-article","created":{"date-parts":[[2024,8,23]],"date-time":"2024-08-23T11:05:52Z","timestamp":1724411152000},"page":"21177-21210","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["A self-adaptive arithmetic optimization algorithm with hybrid search modes for 0\u20131 knapsack problem"],"prefix":"10.1007","volume":"36","author":[{"given":"Mengdie","family":"Lu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haiyan","family":"Lu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xinyu","family":"Hou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qingyuan","family":"Hu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,8,23]]},"reference":[{"key":"10327_CR1","volume-title":"Knapsack problems: algorithms and computer implementations","author":"S Martello","year":"1990","unstructured":"Martello S, Toth P (1990) Knapsack problems: algorithms and computer implementations. John Wiley & Sons Ltd, New York"},{"issue":"10","key":"10327_CR2","doi-asserted-by":"crossref","first-page":"1708","DOI":"10.1016\/j.cor.2009.12.006","volume":"37","author":"S Peeta","year":"2010","unstructured":"Peeta S, Sibel Salman F, Gunnec D, Viswanath K (2010) Pre-disaster investment decisions for strengthening a highway network. Compu Oper Res 37(10):1708\u20131719","journal-title":"Compu Oper Res"},{"issue":"2","key":"10327_CR3","doi-asserted-by":"crossref","first-page":"399","DOI":"10.1016\/j.ejor.2018.07.013","volume":"275","author":"F Brandt","year":"2019","unstructured":"Brandt F, Nickel S (2019) The air cargo load planning problem\u2014a consolidated problem definition and literature review on related problems. Eur J Oper Res 275(2):399\u2013410","journal-title":"Eur J Oper Res"},{"issue":"1","key":"10327_CR4","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1016\/j.future.2008.07.006","volume":"25","author":"DC Vanderster","year":"2009","unstructured":"Vanderster DC, Dimopoulos NJ, Parra-Hernandez R, Sobie RJ (2009) Resource allocation on computational grids using a utility model and the knapsack problem. Future Generat Comput Syst 25(1):35\u201350","journal-title":"Future Generat Comput Syst"},{"key":"10327_CR5","doi-asserted-by":"crossref","first-page":"355","DOI":"10.1016\/j.procs.2016.08.148","volume":"96","author":"Y Gonzalez","year":"2016","unstructured":"Gonzalez Y, Miranda G, Leon C (2016) Multi-objective multi-level filling evolutionary algorithm for the 3d cutting stock problem. Proc Comput Sci 96:355\u2013364","journal-title":"Proc Comput Sci"},{"issue":"1","key":"10327_CR6","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1023\/A:1009642405419","volume":"4","author":"PC Chu","year":"1998","unstructured":"Chu PC, Beasley JE (1998) A genetic algorithm for the multidimensional knapsack problem. J Heuristics 4(1):63\u201386","journal-title":"J Heuristics"},{"issue":"1","key":"10327_CR7","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1007\/s10479-005-3448-8","volume":"139","author":"A Freville","year":"2005","unstructured":"Freville A, Hana S (2005) The multidimensional 0\u20131 knapsack problembounds and computational aspects. Ann Oper Res 139(1):195\u2013227","journal-title":"Ann Oper Res"},{"issue":"5","key":"10327_CR8","doi-asserted-by":"crossref","first-page":"623","DOI":"10.1016\/j.dam.2006.08.007","volume":"155","author":"D Pisinger","year":"2007","unstructured":"Pisinger D (2007) The quadratic knapsack problem-a survey. Discret Appl Math 155(5):623\u2013648","journal-title":"Discret Appl Math"},{"issue":"3","key":"10327_CR9","doi-asserted-by":"crossref","first-page":"901","DOI":"10.1016\/j.ejor.2022.04.036","volume":"304","author":"C Wilbaut","year":"2023","unstructured":"Wilbaut C, Todosijevic R, Hanafi S, Fr\u00e9ville A (2023) Heuristic and exact reduction procedures to solve the discounted 0\u20131 knapsack problem. Eur J Oper Res 304(3):901\u2013911","journal-title":"Eur J Oper Res"},{"key":"10327_CR10","doi-asserted-by":"crossref","DOI":"10.1007\/978-3-540-24777-7","volume-title":"Knapsack problems","author":"H Kellerer","year":"2004","unstructured":"Kellerer H, Pferschy U, Pisinger D (2004) Knapsack problems. Springer, Berlin"},{"issue":"1","key":"10327_CR11","doi-asserted-by":"crossref","first-page":"175","DOI":"10.1016\/0377-2217(94)00013-3","volume":"87","author":"D Pisinger","year":"1995","unstructured":"Pisinger D (1995) An expanding-core algorithm for the exact 0\u20131 knapsack problem. Eur J Oper Res 87(1):175\u2013187","journal-title":"Eur J Oper Res"},{"key":"10327_CR12","doi-asserted-by":"crossref","unstructured":"Shen J, Shigeoka K, Ino F, Hagihara K (2017) An out-of-core branch and bound method for solving the 0\u20131 knapsack problem on a GPU. In: 17th International conference on algorithms and architectures for parallel processing (ICA3PP 2017)","DOI":"10.1007\/978-3-319-65482-9_17"},{"key":"10327_CR13","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1016\/j.cor.2016.11.015","volume":"80","author":"F Della Croce","year":"2017","unstructured":"Della Croce F, Salassa F, Scatamacchia R (2017) An exact approach for the 0\u20131 knapsack problem with setups. Comput Oper Res 80:61\u201367","journal-title":"Comput Oper Res"},{"issue":"16","key":"10327_CR14","doi-asserted-by":"crossref","first-page":"1883","DOI":"10.1016\/j.tcs.2009.12.004","volume":"411","author":"X Li","year":"2010","unstructured":"Li X, Liu T (2010) On exponential time lower bound of knapsack under backtracking. Theor Comput Sci 411(16):1883\u20131888","journal-title":"Theor Comput Sci"},{"issue":"2","key":"10327_CR15","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1007\/s10878-007-9074-4","volume":"15","author":"Y Vimont","year":"2008","unstructured":"Vimont Y, Boussier S, Vasquez M (2008) Reduced costs propagation in an efficient implicit enumeration for the 01 multidimensional knapsack problem. J Comb Opt 15(2):165\u2013178","journal-title":"J Comb Opt"},{"key":"10327_CR16","doi-asserted-by":"crossref","unstructured":"Kennedy J, Eberhart RC (1995) Particle swarm optimization. In: Proceedings of ICNN\u201995 - international conference on neural networks, 4:1942\u20131948","DOI":"10.1109\/ICNN.1995.488968"},{"key":"10327_CR17","volume-title":"Genetic algorithm in search, optimization, and machine learning","author":"DE Goldberg","year":"1989","unstructured":"Goldberg DE (1989) Genetic algorithm in search, optimization, and machine learning. Addison-Wesley, Reading, Massachusetts"},{"key":"10327_CR18","doi-asserted-by":"crossref","first-page":"341","DOI":"10.1023\/A:1008202821328","volume":"11","author":"R Storn","year":"1997","unstructured":"Storn R, Price K (1997) Differential evolution-a simple and efficient heuristic for global optimization over continuous space. J Glob Opt 11:341\u2013359","journal-title":"J Glob Opt"},{"issue":"3","key":"10327_CR19","doi-asserted-by":"crossref","first-page":"459","DOI":"10.1007\/s10898-007-9149-x","volume":"39","author":"D Karaboga","year":"2007","unstructured":"Karaboga D, Basturk B (2007) A powerful and efficient algorithm for numerical function optimization: artificial bee colony (abc) algorithm. J Glob Opt 39(3):459\u2013471","journal-title":"J Glob Opt"},{"key":"10327_CR20","doi-asserted-by":"crossref","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":"10327_CR21","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1016\/j.advengsoft.2013.12.007","volume":"69","author":"S Mirjalili","year":"2014","unstructured":"Mirjalili S, Mirjalili SM, Lewis A (2014) Grey wolf optimizer. Adv Eng Softw 69:46\u201361","journal-title":"Adv Eng Softw"},{"key":"10327_CR22","doi-asserted-by":"crossref","first-page":"120","DOI":"10.1016\/j.knosys.2015.12.022","volume":"96","author":"S Mirjalili","year":"2016","unstructured":"Mirjalili S (2016) Sca: A sine cosine algorithm for solving optimization problems. Knowl Based Syst 96:120\u2013133","journal-title":"Knowl Based Syst"},{"issue":"24","key":"10327_CR23","doi-asserted-by":"crossref","first-page":"18775","DOI":"10.1007\/s00500-023-09147-z","volume":"27","author":"C Sumika","year":"2023","unstructured":"Sumika C, Govind V, Laith A, Anil K (2023) Boosting salp swarm algorithm by opposition-based learning concept and sine cosine algorithm for engineering design problems. Soft Comput 27(24):18775\u201318802","journal-title":"Soft Comput"},{"issue":"2","key":"10327_CR24","first-page":"87","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","journal-title":"Stat Comput"},{"key":"10327_CR25","doi-asserted-by":"crossref","first-page":"300","DOI":"10.1016\/j.future.2020.03.055","volume":"111","author":"S Li","year":"2020","unstructured":"Li S, Chen H, Wang M, Heidari AA, Mirjalili S (2020) Slime mould algorithm: a new method for stochastic optimization. Future Generat Comput Syst 111:300\u2013323","journal-title":"Future Generat Comput Syst"},{"key":"10327_CR26","doi-asserted-by":"crossref","unstructured":"Mohammad\u00a0Abualigah L, Al-diabat M, Al\u00a0Shinwan Mea (2020) Hybrid harmony search algorithm to solve the feature selection for data mining applications. John Wiley & Sons Ltd, New York","DOI":"10.1002\/9781119551621.ch2"},{"key":"10327_CR27","doi-asserted-by":"crossref","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","journal-title":"Appl Soft Comput"},{"issue":"12","key":"10327_CR28","doi-asserted-by":"crossref","first-page":"3265","DOI":"10.1109\/TFUZZ.2020.3003506","volume":"28","author":"D Gao","year":"2020","unstructured":"Gao D, Wang GG, Pedrycz W (2020) Solving fuzzy job-shop scheduling problem using de algorithm improved by a selection mechanism. IEEE Trans Fuzzy Syst 28(12):3265\u20133275","journal-title":"IEEE Trans Fuzzy Syst"},{"key":"10327_CR29","doi-asserted-by":"crossref","first-page":"1345","DOI":"10.1007\/s00521-021-06453-1","volume":"34","author":"MMA Ali","year":"2022","unstructured":"Ali MMA, Jamali A, Asgharnia A, Ansari R, Mallipeddi R (2022) Multi-objective lyapunov-based controller design for nonlinear systems via genetic programming. Neural Comput Appl 34:1345\u20131357","journal-title":"Neural Comput Appl"},{"issue":"7","key":"10327_CR30","doi-asserted-by":"crossref","first-page":"9073","DOI":"10.1007\/s12652-022-04412-9","volume":"14","author":"C Sumika","year":"2023","unstructured":"Sumika C, Govind V, Anil K (2023) Approximating parameters of photovoltaic models using an amended reptile search algorithm. J Amb Intel Hum Comp 14(7):9073\u20139088","journal-title":"J Amb Intel Hum Comp"},{"issue":"1","key":"10327_CR31","first-page":"1","volume":"10","author":"M Abdel-Basset","year":"2017","unstructured":"Abdel-Basset M, El-Shahat D, Sangaiah AK (2017) A modified nature inspired meta-heuristic whale optimization algorithm for solving 0\u20131 knapsack problem. Int J Mach Learn Cybernet 10(1):1\u201320","journal-title":"Int J Mach Learn Cybernet"},{"key":"10327_CR32","volume":"151","author":"M Abdel-Basset","year":"2021","unstructured":"Abdel-Basset M, Mohamed R, Chakrabortty RK, Ryan M, Mirjalili S (2021) New binary marine predators optimization algorithms for 0\u20131 knapsack problems. Comput. Ind Eng 151:106949","journal-title":"Comput. Ind Eng"},{"key":"10327_CR33","doi-asserted-by":"crossref","first-page":"5477","DOI":"10.1007\/s00521-018-3375-7","volume":"31","author":"M Abdel-Basset","year":"2019","unstructured":"Abdel-Basset M, El-Shahat D, El-Henawy I (2019) Solving 0\u20131 knapsack problem by binary flower pollination algorithm. Neural Comput Appl 31:5477\u20135495","journal-title":"Neural Comput Appl"},{"key":"10327_CR34","doi-asserted-by":"crossref","first-page":"3423","DOI":"10.1007\/s00366-021-01470-z","volume":"38","author":"B Abdollahzadeh","year":"2022","unstructured":"Abdollahzadeh B, Barshandeh S, Javadi H, Epicoco N (2022) An enhanced binary slime mould algorithm for solving the 0\u20131 knapsack problem. Eng Comput 38:3423\u20133444","journal-title":"Eng Comput"},{"issue":"5","key":"10327_CR35","doi-asserted-by":"crossref","first-page":"5751","DOI":"10.1007\/s10489-021-02717-4","volume":"52","author":"Z Shu","year":"2022","unstructured":"Shu Z, Ye Z, Zong X, Liu S, Zhang D, Wang C, Wang M (2022) A modified hybrid rice optimization algorithm for solving 0\u20131 knapsack problem. Appl Intell 52(5):5751\u20135769","journal-title":"Appl Intell"},{"key":"10327_CR36","doi-asserted-by":"crossref","first-page":"13359","DOI":"10.1007\/s00521-023-08358-7","volume":"35","author":"KM Sallam","year":"2023","unstructured":"Sallam KM, Abohany AA, Rizk-Allah RM (2023) An enhanced multi-operator differential evolution algorithm for tackling knapsack optimization problem. Neural Comput Appl 35:13359\u201313386","journal-title":"Neural Comput Appl"},{"key":"10327_CR37","doi-asserted-by":"crossref","first-page":"13277","DOI":"10.1007\/s00500-022-07518-6","volume":"26","author":"M Tanhaeean","year":"2022","unstructured":"Tanhaeean M, Tavakkoli-Moghaddam R, Akbari AH (2022) Boxing match algorithm: a new meta-heuristic algorithm. Soft Comput 26:13277\u201313299","journal-title":"Soft Comput"},{"key":"10327_CR38","doi-asserted-by":"crossref","DOI":"10.1016\/j.cma.2020.113609","volume":"376","author":"L Abualigah","year":"2021","unstructured":"Abualigah L, Diabat A, Mirjalili S, Abd Elaziz M, Gandomi AH (2021) The arithmetic optimization algorithm. Comput Methods Appl Mech Eng 376:113609","journal-title":"Comput Methods Appl Mech Eng"},{"key":"10327_CR39","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2023.110640","volume":"275","author":"Z Zhuang","year":"2023","unstructured":"Zhuang Z, Pan JS, Li J, Chu SC (2023) Parallel binary arithmetic optimization algorithm and its application for feature selection. Knowl Based Syst 275:110640. https:\/\/doi.org\/10.1016\/j.knosys.2023.110640","journal-title":"Knowl Based Syst"},{"issue":"7","key":"10327_CR40","doi-asserted-by":"crossref","first-page":"1155","DOI":"10.3390\/pr9071155","volume":"9","author":"L Abualigah","year":"2021","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. Processes 9(7):1155","journal-title":"Processes"},{"issue":"2","key":"10327_CR41","doi-asserted-by":"crossref","first-page":"202","DOI":"10.3390\/sym14020202","volume":"14","author":"A Mancilla","year":"2022","unstructured":"Mancilla A, Garc\u00eda-Valdez M, Castillo O, Merelo-Guerv\u00f3s JJ (2022) Optimal fuzzy controller design for autonomous robot path tracking using population-based metaheuristics. Symmetry 14(2):202","journal-title":"Symmetry"},{"issue":"1","key":"10327_CR42","doi-asserted-by":"crossref","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","journal-title":"IEEE Trans Evol Comput"},{"key":"10327_CR43","doi-asserted-by":"crossref","first-page":"748","DOI":"10.1016\/j.istruc.2021.11.012","volume":"35","author":"A Kaveh","year":"2022","unstructured":"Kaveh A, Hamedani KB (2022) Improved arithmetic optimization algorithm and its application to discrete structural optimization. Structures 35:748\u2013764","journal-title":"Structures"},{"key":"10327_CR44","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2022.108833","volume":"248","author":"L Abualigah","year":"2022","unstructured":"Abualigah L, Almotairi KH, Al-qaness MAA, Ewees AA, Yousri D, Elaziz MA, Nadimi-Shahraki MH (2022) Efficient text document clustering approach using multi-search arithmetic optimization algorithm. Knowl Based Syst 248:108833","journal-title":"Knowl Based Syst"},{"key":"10327_CR45","doi-asserted-by":"crossref","first-page":"1833","DOI":"10.1007\/s10845-021-01877-x","volume":"34","author":"L Abualigah","year":"2023","unstructured":"Abualigah L, Diabat A (2023) Improved multi-core arithmetic optimization algorithm-based ensemble mutation for multidisciplinary applications. J Intell Manuf 34:1833\u20131874","journal-title":"J Intell Manuf"},{"key":"10327_CR46","doi-asserted-by":"crossref","first-page":"8823","DOI":"10.1007\/s00521-022-06906-1","volume":"34","author":"L Abualigah","year":"2022","unstructured":"Abualigah L, Ewees AA, Al-qaness MAAea (2022) Boosting arithmetic optimization algorithm by sine cosine algorithm and levy flight distribution for solving engineering optimization problems. Neural Comput Appl 34:8823\u20138852","journal-title":"Neural Comput Appl"},{"issue":"5","key":"10327_CR47","doi-asserted-by":"crossref","first-page":"6234","DOI":"10.1007\/s11227-021-04105-8","volume":"78","author":"C Sumika","year":"2022","unstructured":"Sumika C, Govind V, Anil K (2022) A symbiosis of arithmetic optimizer with slime mould algorithm for improving global optimization and conventional design problem. J Supercomput 78(5):6234\u20136274","journal-title":"J Supercomput"},{"key":"10327_CR48","doi-asserted-by":"crossref","first-page":"1253","DOI":"10.1007\/s00521-017-3091-8","volume":"31","author":"M Ramadas","year":"2019","unstructured":"Ramadas M, Pant M, Abraham A, Kumar S (2019) Segmentation of weather radar image based on hazard severity using rde: reconstructed mutation strategy for differential evolution algorithm. Neural Comput Appl 31:1253\u20131261","journal-title":"Neural Comput Appl"},{"key":"10327_CR49","doi-asserted-by":"crossref","first-page":"6139","DOI":"10.1007\/s00521-019-04104-0","volume":"32","author":"M Ramadas","year":"2020","unstructured":"Ramadas M, Abraham A (2020) Detecting tumours by segmenting mri images using transformed differential evolution algorithm with kapur\u2019s thresholding. Neural Comput Appl 32:6139\u20136149","journal-title":"Neural Comput Appl"},{"key":"10327_CR50","volume":"118","author":"C Sumika","year":"2023","unstructured":"Sumika C, Govind V (2023) A synergy of an evolutionary algorithm with slime mould algorithm through series and parallel construction for improving global optimization and conventional design problem. Eng Appl Artif Intell 118:105650","journal-title":"Eng Appl Artif Intell"},{"key":"10327_CR51","doi-asserted-by":"crossref","first-page":"192","DOI":"10.1016\/j.ins.2021.11.073","volume":"586","author":"V Osuna-Enciso","year":"2022","unstructured":"Osuna-Enciso V, Cuevas E, Morales Casta\u00f1eda B (2022) A diversity metric for population-based metaheuristic algorithms. Inf Sci 586:192\u2013208","journal-title":"Inf Sci"},{"issue":"9","key":"10327_CR52","doi-asserted-by":"crossref","first-page":"2649","DOI":"10.1142\/S0218127408021877","volume":"18","author":"AA Dubkov","year":"2008","unstructured":"Dubkov AA, Spagnolo B, Uchaikin VV (2008) Levy flight superdiffusion: an introduction. Int J Bifurcat Chaos 18(9):2649\u20132672","journal-title":"Int J Bifurcat Chaos"},{"issue":"12","key":"10327_CR53","doi-asserted-by":"crossref","first-page":"3707","DOI":"10.1007\/s00521-017-2952-5","volume":"30","author":"S Amirsadri","year":"2018","unstructured":"Amirsadri S, Mousavirad SJ, Ebrahimpour-Komleh H (2018) A levy flight-based grey wolf optimizer combined with back-propagation algorithm for neural network training. Neural Comput Appl 30(12):3707\u20133720","journal-title":"Neural Comput Appl"},{"key":"10327_CR54","doi-asserted-by":"crossref","first-page":"288","DOI":"10.1016\/j.conbuildmat.2016.05.072","volume":"119","author":"GF Scimemi","year":"2016","unstructured":"Scimemi GF, Turetta T, Celauro C (2016) Backcalculation of airport pavement moduli and thickness using the levy ant colony optimization algorithm. Constr Build Mater 119:288\u2013295","journal-title":"Constr Build Mater"},{"key":"10327_CR55","doi-asserted-by":"crossref","first-page":"697","DOI":"10.1016\/j.asoc.2018.09.019","volume":"73","author":"SN Chegini","year":"2018","unstructured":"Chegini SN, Bagheri A, Najafi F (2018) Psoscalf: A new hybrid pso based on sine cosine algorithm and levy flight for solving optimization problems. Appl Soft Comput 73:697\u2013726","journal-title":"Appl Soft Comput"},{"issue":"5","key":"10327_CR56","doi-asserted-by":"crossref","first-page":"4677","DOI":"10.1103\/PhysRevE.49.4677","volume":"49","author":"RN Mantegna","year":"1994","unstructured":"Mantegna RN (1994) Accurate algorithm for numerical simulation of levy stable stochastic processes. Phys Rev E 49(5):4677\u20134683","journal-title":"Phys Rev E"},{"key":"10327_CR57","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.swevo.2012.09.002","volume":"9","author":"S Mirjalili","year":"2013","unstructured":"Mirjalili S, Lewis A (2013) S-shaped versus v-shaped transfer functions for binary particle swarm optimization. Swarm Evol Comput 9:1\u201314","journal-title":"Swarm Evol Comput"},{"key":"10327_CR58","volume":"113","author":"Y Yang","year":"2022","unstructured":"Yang Y, Gao Y, Tan S, Zhao S, Wu J, Gao S, Zhang T, Tian Y, Wang Y (2022) An opposition learning and spiral modelling based arithmetic optimization algorithm for global continuous optimization problems. Eng Appl Artif Intell 113:104981","journal-title":"Eng Appl Artif Intell"},{"key":"10327_CR59","doi-asserted-by":"crossref","first-page":"981","DOI":"10.1007\/s12065-022-00711-4","volume":"16","author":"SB Aydemir","year":"2023","unstructured":"Aydemir SB (2023) A novel arithmetic optimization algorithm based on chaotic maps for global optimization. Evol Intell 16:981\u2013996","journal-title":"Evol Intell"},{"key":"10327_CR60","volume":"394","author":"G Hu","year":"2022","unstructured":"Hu G, Zhong J, Du B, Wei G (2022) An enhanced hybrid arithmetic optimization algorithm for engineering applications. Comput Methods Appl Mech Eng 394:114901","journal-title":"Comput Methods Appl Mech Eng"},{"key":"10327_CR61","doi-asserted-by":"crossref","unstructured":"Kulkarni AJ, Krishnasamy G, Abraham A (2017) Solution to 0-1 knapsack problem using cohort intelligence algorithm. In: Cohort intelligence: a socio-inspired optimization method, pp 55\u201374. Springer, Berlin","DOI":"10.1007\/978-3-319-44254-9_5"},{"key":"10327_CR62","doi-asserted-by":"crossref","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 Generat Comput Syst 97:849\u2013872","journal-title":"Future Generat Comput Syst"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-024-10327-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00521-024-10327-7\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-024-10327-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,28]],"date-time":"2024-09-28T16:06:40Z","timestamp":1727539600000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00521-024-10327-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,8,23]]},"references-count":62,"journal-issue":{"issue":"33","published-print":{"date-parts":[[2024,11]]}},"alternative-id":["10327"],"URL":"https:\/\/doi.org\/10.1007\/s00521-024-10327-7","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,8,23]]},"assertion":[{"value":"21 October 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 July 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"23 August 2024","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"All the authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}