{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,27]],"date-time":"2026-02-27T14:24:25Z","timestamp":1772202265001,"version":"3.50.1"},"reference-count":195,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2022,9,21]],"date-time":"2022-09-21T00:00:00Z","timestamp":1663718400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2022,9,21]],"date-time":"2022-09-21T00:00:00Z","timestamp":1663718400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Complex Intell. Syst."],"published-print":{"date-parts":[[2023,4]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>The existing slime mould algorithm clones the uniqueness of the phase of oscillation of slime mould conduct and exhibits slow convergence in local search space due to poor exploitation phase. This research work exhibits to discover the best solution for objective function by commingling slime mould algorithm and simulated annealing algorithm for better variation of parameters and named as hybridized slime mould algorithm\u2013simulated annealing algorithm. The simulated annealing algorithm improves and accelerates the effectiveness of slime mould technique as well as assists to take off from the local optimum. To corroborate the worth and usefulness of the introduced strategy, nonconvex, nonlinear, and typical engineering design difficulties were analyzed for standard benchmarks and interdisciplinary engineering design concerns. The proposed technique version is used to evaluate six, five, five unimodal, multimodal and fixed-dimension benchmark functions, respectively, also including 11 kinds of interdisciplinary engineering design difficulties. The technique\u2019s outcomes were compared to the results of other on-hand optimization methods, and the experimental results show that the suggested approach outperforms the other optimization techniques.<\/jats:p>","DOI":"10.1007\/s40747-022-00852-0","type":"journal-article","created":{"date-parts":[[2022,9,21]],"date-time":"2022-09-21T05:02:30Z","timestamp":1663736550000},"page":"1525-1582","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Hybridizing slime mould algorithm with simulated annealing algorithm: a hybridized statistical approach for numerical and engineering design problems"],"prefix":"10.1007","volume":"9","author":[{"given":"Leela Kumari","family":"Ch","sequence":"first","affiliation":[]},{"given":"Vikram Kumar","family":"Kamboj","sequence":"additional","affiliation":[]},{"given":"S. K.","family":"Bath","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,9,21]]},"reference":[{"issue":"May","key":"852_CR1","doi-asserted-by":"publisher","first-page":"927","DOI":"10.1016\/j.enconman.2019.05.057","volume":"195","author":"H Chen","year":"2019","unstructured":"Chen H, Jiao S, Heidari AA, Wang M, Chen X, Zhao X (2019) An opposition-based sine cosine approach with local search for parameter estimation of photovoltaic models. Energy Convers Manag 195(May):927\u2013942. https:\/\/doi.org\/10.1016\/j.enconman.2019.05.057","journal-title":"Energy Convers Manag"},{"key":"852_CR2","doi-asserted-by":"publisher","unstructured":"Osher SJ et al (2018) Laplacian smooth gradient descent. pp 1\u201328. https:\/\/doi.org\/10.48550\/ARXIV.1806.06317","DOI":"10.48550\/ARXIV.1806.06317"},{"key":"852_CR3","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. Future Gener Comput Syst 111:300\u2013323. https:\/\/doi.org\/10.1016\/j.future.2020.03.055","journal-title":"Future Gener Comput Syst"},{"issue":"1","key":"852_CR4","doi-asserted-by":"publisher","first-page":"1667","DOI":"10.3233\/JIFS-201755","volume":"40","author":"K Sun","year":"2021","unstructured":"Sun K, Jia H, Li Y, Jiang Z (2021) Hybrid improved slime mould algorithm with adaptive \u03b2 hill climbing for numerical optimization. J Intell Fuzzy Syst 40(1):1667\u20131679. https:\/\/doi.org\/10.3233\/JIFS-201755","journal-title":"J Intell Fuzzy Syst"},{"key":"852_CR5","doi-asserted-by":"publisher","DOI":"10.1088\/1742-6596\/1617\/1\/012034","author":"ZM Gao","year":"2020","unstructured":"Gao ZM, Zhao J, Yang Y, Tian XJ (2020) The hybrid grey wolf optimization-slime mould algorithm. J Phys Conf Ser. https:\/\/doi.org\/10.1088\/1742-6596\/1617\/1\/012034","journal-title":"J Phys Conf Ser"},{"key":"852_CR6","doi-asserted-by":"publisher","DOI":"10.1088\/1742-6596\/1617\/1\/012033","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. https:\/\/doi.org\/10.1088\/1742-6596\/1617\/1\/012033","journal-title":"J Phys Conf Ser"},{"key":"852_CR7","doi-asserted-by":"publisher","DOI":"10.1088\/1742-6596\/1631\/1\/012071","author":"J Zhao","year":"2020","unstructured":"Zhao J, Gao ZM (2020) The chaotic slime mould algorithm with Chebyshev map. J Phys Conf Ser. https:\/\/doi.org\/10.1088\/1742-6596\/1631\/1\/012071","journal-title":"J Phys Conf Ser"},{"key":"852_CR8","doi-asserted-by":"publisher","unstructured":"Cui Z, Hou X, Zhou H, Lian W, Wu J (2020) Modified slime mould algorithm via Levy flight, November, pp 1109\u20131113. https:\/\/doi.org\/10.1109\/cisp-bmei51763.2020.9263669.","DOI":"10.1109\/cisp-bmei51763.2020.9263669"},{"issue":"2","key":"852_CR9","doi-asserted-by":"publisher","first-page":"435","DOI":"10.1177\/01423312211037967","volume":"44","author":"D Izci","year":"2021","unstructured":"Izci D, Ekinci S, Zeynelgil HL, Hedley J (2021) Performance evaluation of a novel improved slime mould algorithm for direct current motor and automatic voltage regulator systems. Trans Inst Meas Control 44(2):435\u2013456. https:\/\/doi.org\/10.1177\/01423312211037967","journal-title":"Trans Inst Meas Control"},{"key":"852_CR10","doi-asserted-by":"publisher","DOI":"10.1088\/1742-6596\/1682\/1\/012029","author":"J Zhao","year":"2020","unstructured":"Zhao J, Gao ZM (2020) The hybridized Harris hawk optimization and slime mould algorithm. J Phys Conf Ser. https:\/\/doi.org\/10.1088\/1742-6596\/1682\/1\/012029","journal-title":"J Phys Conf Ser"},{"key":"852_CR11","doi-asserted-by":"publisher","DOI":"10.1088\/1742-6596\/1631\/1\/012083","author":"ZM Gao","year":"2020","unstructured":"Gao ZM, Zhao J, Li SR (2020) The improved slime mould algorithm with cosine controlling parameters. J Phys Conf Ser. https:\/\/doi.org\/10.1088\/1742-6596\/1631\/1\/012083","journal-title":"J Phys Conf Ser"},{"key":"852_CR12","doi-asserted-by":"publisher","unstructured":"Monismith DR, Mayfield BE (2008) Slime mould as a model for numerical optimization. 2008 IEEE Swarm Intell. Symp. SIS 2008, no. January. https:\/\/doi.org\/10.1109\/SIS.2008.4668295","DOI":"10.1109\/SIS.2008.4668295"},{"key":"852_CR13","doi-asserted-by":"publisher","first-page":"3229","DOI":"10.1109\/ACCESS.2020.3047936","volume":"9","author":"M Premkumar","year":"2021","unstructured":"Premkumar M, Jangir P, Sowmya R, Alhelou HH, Heidari AA, Chen H (2021) MOSMA: multi-objective slime mould algorithm based on elitist non-dominated sorting. IEEE Access 9:3229\u20133248. https:\/\/doi.org\/10.1109\/ACCESS.2020.3047936","journal-title":"IEEE Access"},{"issue":"3\u20134","key":"852_CR14","doi-asserted-by":"publisher","first-page":"183","DOI":"10.1007\/s11721-011-0063-y","volume":"5","author":"K Li","year":"2011","unstructured":"Li K, Torres CE, Thomas K, Rossi LF, Shen CC (2011) Slime mould inspired routing protocols for wireless sensor networks. Swarm Intell 5(3\u20134):183\u2013223. https:\/\/doi.org\/10.1007\/s11721-011-0063-y","journal-title":"Swarm Intell"},{"key":"852_CR15","doi-asserted-by":"publisher","unstructured":"Qian T, Zhang Z, Gao C, Wu Y, Liu Y (2013) An ant colony system based on the physarum network. Lect. Notes Comput. Sci. (including Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinformatics), vol 7928 LNCS, no PART 1, pp 297\u2013305. https:\/\/doi.org\/10.1007\/978-3-642-38703-6_35","DOI":"10.1007\/978-3-642-38703-6_35"},{"key":"852_CR16","doi-asserted-by":"publisher","unstructured":"Schmickl T, Crailsheim K (2007) A navigation algorithm for swarm robotics inspired by slime mould aggregation. Lect. Notes Comput. Sci. (including Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinformatics), vol 4433 LNCS, no September, pp 1\u201313. https:\/\/doi.org\/10.1007\/978-3-540-71541-2_1","DOI":"10.1007\/978-3-540-71541-2_1"},{"key":"852_CR17","doi-asserted-by":"publisher","unstructured":"Becker M (2016) On the efficiency of nature-inspired algorithms for generation of fault-tolerant graphs. In: Proceedings of 2015 IEEE international conference system man, cybernetics. SMC 2015, no. September, pp 1657\u20131663. https:\/\/doi.org\/10.1109\/SMC.2015.292","DOI":"10.1109\/SMC.2015.292"},{"issue":"1","key":"852_CR18","doi-asserted-by":"publisher","first-page":"30","DOI":"10.1504\/IJICA.2020.105316","volume":"11","author":"A Brabazon","year":"2020","unstructured":"Brabazon A, McGarraghy S (2020) Slime mould foraging: an inspiration for algorithmic design. Int J Innov Comput Appl 11(1):30\u201345. https:\/\/doi.org\/10.1504\/IJICA.2020.105316","journal-title":"Int J Innov Comput Appl"},{"key":"852_CR19","doi-asserted-by":"publisher","unstructured":"Suid MH, Ahmad MA, Ismail MRTR, Ghazali MR, Irawan A, Tumari MZ (2019) An improved sine cosine algorithm for solving optimization problems. In: Proceedings of 2018 IEEE conference system process control. ICSPC 2018, pp 209\u2013213. https:\/\/doi.org\/10.1109\/SPC.2018.8703982","DOI":"10.1109\/SPC.2018.8703982"},{"issue":"13","key":"852_CR20","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":"852_CR21","doi-asserted-by":"publisher","first-page":"425","DOI":"10.2528\/PIER07082403","volume":"77","author":"RA Formato","year":"2007","unstructured":"Formato RA (2007) Central force optimization: a new metaheuristic with applications in applied electromagnetics. Prog Electromagn Res 77:425\u2013491. https:\/\/doi.org\/10.2528\/PIER07082403","journal-title":"Prog Electromagn Res"},{"issue":"1","key":"852_CR22","doi-asserted-by":"publisher","first-page":"137","DOI":"10.24425\/aoa.2019.126360","volume":"44","author":"MR Mosavi","year":"2019","unstructured":"Mosavi MR, Khishe M, Naseri MJ, Parvizi GR, Ayat M (2019) Multi-layer perceptron neural network utilizing adaptive best-mass gravitational search algorithm to classify sonar dataset. Arch Acoust 44(1):137\u2013151. https:\/\/doi.org\/10.24425\/aoa.2019.126360","journal-title":"Arch Acoust"},{"issue":"3\u20134","key":"852_CR23","doi-asserted-by":"publisher","first-page":"267","DOI":"10.1007\/s00707-009-0270-4","volume":"213","author":"A Kaveh","year":"2010","unstructured":"Kaveh A, Talatahari S (2010) A novel heuristic optimization method: charged system search. Acta Mech 213(3\u20134):267\u2013289. https:\/\/doi.org\/10.1007\/s00707-009-0270-4","journal-title":"Acta Mech"},{"issue":"2","key":"852_CR24","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":"852_CR25","first-page":"194","volume":"92","author":"JR Koza","year":"1992","unstructured":"Koza JR, Rice JP (1992) Automatic programming of robots using genetic programming. Proc Tenth Natl Conf Artif Intell 92:194\u2013207","journal-title":"Proc Tenth Natl Conf Artif Intell"},{"issue":"2","key":"852_CR26","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 Comput 3(2):82\u2013102","journal-title":"IEEE Trans Evol Comput"},{"issue":"6","key":"852_CR27","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"},{"key":"852_CR28","unstructured":"Fleetwood K (2004) An introduction to differential evolution. In: Proceedings of mathematics and statistics of complex systems (MASCOS) one day symposium, 26th November, Brisbane, Australia. pp 785\u2013791"},{"key":"852_CR29","doi-asserted-by":"publisher","first-page":"43","DOI":"10.1007\/978-3-319-93025-1_4","volume":"780","author":"S Mirjalili","year":"2019","unstructured":"Mirjalili S (2019) Genetic algorithm. Stud Comput Intell 780:43\u201355. https:\/\/doi.org\/10.1007\/978-3-319-93025-1_4","journal-title":"Stud Comput Intell"},{"key":"852_CR30","doi-asserted-by":"publisher","DOI":"10.1109\/tevc.2020.3034769","author":"X He","year":"2020","unstructured":"He X, Zheng Z, Zhou Y (2020) MMES: mixture model based evolution strategy for large-scale optimization. IEEE Trans Evol Comput. https:\/\/doi.org\/10.1109\/tevc.2020.3034769","journal-title":"IEEE Trans Evol Comput"},{"key":"852_CR31","doi-asserted-by":"publisher","DOI":"10.1016\/j.enbuild.2020.110023","author":"W Qiao","year":"2020","unstructured":"Qiao W, Moayedi H, Foong LK (2020) Nature-inspired hybrid techniques of IWO, DA, ES, GA, and ICA, validated through a k-fold validation process predicting monthly natural gas consumption. Energy Build. https:\/\/doi.org\/10.1016\/j.enbuild.2020.110023","journal-title":"Energy Build"},{"key":"852_CR32","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-58069-7_38","author":"G Beni","year":"1993","unstructured":"Beni G, Wang J (1993) Swarm intelligence in cellular robotic systems. Robot Biol Syst Towar New Bionics. https:\/\/doi.org\/10.1007\/978-3-642-58069-7_38","journal-title":"Robot Biol Syst Towar New Bionics"},{"issue":"15","key":"852_CR33","doi-asserted-by":"publisher","first-page":"6249","DOI":"10.1007\/s00500-018-3282-y","volume":"23","author":"MM Mafarja","year":"2019","unstructured":"Mafarja MM, Mirjalili S (2019) Hybrid binary ant lion optimizer with rough set and approximate entropy reducts for feature selection. Soft Comput 23(15):6249\u20136265. https:\/\/doi.org\/10.1007\/s00500-018-3282-y","journal-title":"Soft Comput"},{"key":"852_CR34","doi-asserted-by":"publisher","first-page":"228","DOI":"10.1016\/j.knosys.2015.07.006","volume":"89","author":"S Mirjalili","year":"2015","unstructured":"Mirjalili S (2015) Moth-flame optimization algorithm: a novel nature-inspired heuristic paradigm. Knowl Based Syst 89:228\u2013249. https:\/\/doi.org\/10.1016\/j.knosys.2015.07.006","journal-title":"Knowl Based Syst"},{"issue":"3","key":"852_CR35","doi-asserted-by":"publisher","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 Optim 39(3):459\u2013471. https:\/\/doi.org\/10.1007\/s10898-007-9149-x","journal-title":"J Glob Optim"},{"key":"852_CR36","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"},{"key":"852_CR37","doi-asserted-by":"publisher","first-page":"69","DOI":"10.1016\/j.knosys.2011.07.001","volume":"26","author":"WT Pan","year":"2012","unstructured":"Pan WT (2012) A new fruit fly optimization algorithm: taking the financial distress model as an example. Knowl Based Syst 26:69\u201374. https:\/\/doi.org\/10.1016\/j.knosys.2011.07.001","journal-title":"Knowl Based Syst"},{"issue":"2\u20133","key":"852_CR38","doi-asserted-by":"publisher","first-page":"243","DOI":"10.1016\/j.tcs.2005.05.020","volume":"344","author":"M Dorigo","year":"2005","unstructured":"Dorigo M, Blum C (2005) Ant colony optimization theory: a survey. Theor Comput Sci 344(2\u20133):243\u2013278. https:\/\/doi.org\/10.1016\/j.tcs.2005.05.020","journal-title":"Theor Comput Sci"},{"key":"852_CR39","doi-asserted-by":"publisher","DOI":"10.1016\/j.advengsoft.2013.12.007","author":"S Mirjalili","year":"2014","unstructured":"Mirjalili S, Mirjalili SM, Lewis A (2014) Grey wolf optimizer. Adv Eng Softw. https:\/\/doi.org\/10.1016\/j.advengsoft.2013.12.007","journal-title":"Adv Eng Softw"},{"issue":"1","key":"852_CR40","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":"852_CR41","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/BF02078647","volume":"41","author":"F Glover","year":"1993","unstructured":"Glover F, Taillard E (1993) A user\u2019s guide to tabu search. Ann Oper Res 41(1):1\u201328. https:\/\/doi.org\/10.1007\/BF02078647","journal-title":"Ann Oper Res"},{"issue":"2","key":"852_CR42","doi-asserted-by":"publisher","first-page":"157","DOI":"10.1007\/s00500-008-0303-2","volume":"13","author":"L Lin","year":"2009","unstructured":"Lin L, Gen M (2009) Auto-tuning strategy for evolutionary algorithms: Balancing between exploration and exploitation. Soft Comput 13(2):157\u2013168. https:\/\/doi.org\/10.1007\/s00500-008-0303-2","journal-title":"Soft Comput"},{"key":"852_CR43","doi-asserted-by":"publisher","unstructured":"Whitley D, Rowe J (2008) Focused no free lunch theorems. GECCO\u201908 Proceedings of 10th annual conference genetics evolution computing. pp 811\u2013818. https:\/\/doi.org\/10.1145\/1389095.1389254","DOI":"10.1145\/1389095.1389254"},{"issue":"1","key":"852_CR44","doi-asserted-by":"publisher","first-page":"67","DOI":"10.1109\/4235.585893","volume":"1","author":"DH Wolpert","year":"1997","unstructured":"Wolpert DH, Macready WG (1997) No free lunch theorems for optimization. IEEE Trans Evol Comput 1(1):67\u201382. https:\/\/doi.org\/10.1109\/4235.585893","journal-title":"IEEE Trans Evol Comput"},{"issue":"1","key":"852_CR45","doi-asserted-by":"publisher","first-page":"426","DOI":"10.2991\/ijcis.2018.125905658","volume":"12","author":"KW Huang","year":"2018","unstructured":"Huang KW, Wu ZX (2018) CPO: a crow particle optimization algorithm. Int J Comput Intell Syst 12(1):426\u2013435. https:\/\/doi.org\/10.2991\/ijcis.2018.125905658","journal-title":"Int J Comput Intell Syst"},{"key":"852_CR46","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":"852_CR47","doi-asserted-by":"publisher","first-page":"106903","DOI":"10.1016\/j.asoc.2020.106903","volume":"99","author":"VKRA Kalananda","year":"2021","unstructured":"Kalananda VKRA, Komanapalli VLN (2021) A combinatorial social group whale optimization algorithm for numerical and engineering optimization problems. Appl Soft Comput 99:106903. https:\/\/doi.org\/10.1016\/j.asoc.2020.106903","journal-title":"Appl Soft Comput"},{"issue":"March","key":"852_CR48","doi-asserted-by":"publisher","first-page":"175","DOI":"10.1016\/j.knosys.2018.03.011","volume":"150","author":"G Dhiman","year":"2018","unstructured":"Dhiman G, Kumar V (2018) Multi-objective spotted hyena optimizer: a multi-objective optimization algorithm for engineering problems. Knowl Based Syst 150(March):175\u2013197. https:\/\/doi.org\/10.1016\/j.knosys.2018.03.011","journal-title":"Knowl Based Syst"},{"key":"852_CR49","doi-asserted-by":"publisher","DOI":"10.1111\/exsy.12642","author":"K Hu","year":"2020","unstructured":"Hu K, Jiang H, Ji CG, Pan Z (2020) A modified butterfly optimization algorithm: an adaptive algorithm for global optimization and the support vector machine. Expert Syst. https:\/\/doi.org\/10.1111\/exsy.12642","journal-title":"Expert Syst"},{"issue":"12","key":"852_CR50","doi-asserted-by":"publisher","first-page":"7031","DOI":"10.1007\/s00521-020-05475-5","volume":"33","author":"AB Krishna","year":"2021","unstructured":"Krishna AB, Saxena S, Kamboj VK (2021) A novel statistical approach to numerical and multidisciplinary design optimization problems using pattern search inspired Harris hawks optimizer. Neural Comput Appl 33(12):7031\u20137072. https:\/\/doi.org\/10.1007\/s00521-020-05475-5 (ISSN: 0941-0643, 1433-3058)","journal-title":"Neural Comput Appl"},{"issue":"7","key":"852_CR51","doi-asserted-by":"publisher","first-page":"2625","DOI":"10.1007\/s12652-019-01324-z","volume":"11","author":"V Kumar","year":"2020","unstructured":"Kumar V, Kaur A (2020) Binary spotted hyena optimizer and its application to feature selection. J Ambient Intell Humaniz Comput 11(7):2625\u20132645. https:\/\/doi.org\/10.1007\/s12652-019-01324-z","journal-title":"J Ambient Intell Humaniz Comput"},{"issue":"6","key":"852_CR52","first-page":"386","volume":"9","author":"H Zamani","year":"2020","unstructured":"Zamani H, Nadimi-shahraki MH (2020) Enhancement of Bernstain-search differential evolution algorithm to solve constrained engineering problems. Int J Comput Sci Eng (IJCSE) 9(6):386\u2013396","journal-title":"Int J Comput Sci Eng (IJCSE)"},{"key":"852_CR53","doi-asserted-by":"publisher","DOI":"10.1007\/s11831-020-09443-z","author":"Z Meng","year":"2020","unstructured":"Meng Z, Li G, Wang X, Sait SM, Y\u0131ld\u0131z AR (2020) A comparative study of metaheuristic algorithms for reliability-based design optimization problems. Arch Comput Methods Eng. https:\/\/doi.org\/10.1007\/s11831-020-09443-z","journal-title":"Arch Comput Methods Eng"},{"key":"852_CR54","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2019.106018","volume":"89","author":"VK Kamboj","year":"2020","unstructured":"Kamboj VK, Nandi A, Bhadoria A, Sehgal S (2020) An intensify Harris Hawks optimizer for numerical and engineering optimization problems. Appl Soft Comput J 89:106018. https:\/\/doi.org\/10.1016\/j.asoc.2019.106018","journal-title":"Appl Soft Comput J"},{"key":"852_CR55","doi-asserted-by":"publisher","DOI":"10.1007\/s10489-021-03155-y","author":"Y Che","year":"2022","unstructured":"Che Y, He D (2022) An enhanced seagull optimization algorithm for solving engineering optimization problems. Appl Intell. https:\/\/doi.org\/10.1007\/s10489-021-03155-y","journal-title":"Appl Intell"},{"key":"852_CR56","doi-asserted-by":"publisher","DOI":"10.1007\/s10489-021-02982-3","author":"Z Li","year":"2022","unstructured":"Li Z, Zhang Q, He Y (2022) Modified group theory-based optimization algorithms for numerical optimization. Appl Intell. https:\/\/doi.org\/10.1007\/s10489-021-02982-3","journal-title":"Appl Intell"},{"key":"852_CR57","doi-asserted-by":"publisher","DOI":"10.1007\/s13369-021-06446-1","author":"A Srivastava","year":"2022","unstructured":"Srivastava A, Das DK (2022) Criminal search optimization algorithm: a population-based meta-heuristic optimization technique to solve real-world optimization problems. Arab J Sci Eng. https:\/\/doi.org\/10.1007\/s13369-021-06446-1","journal-title":"Arab J Sci Eng"},{"key":"852_CR58","doi-asserted-by":"publisher","DOI":"10.1108\/mmms-10-2021-0174","author":"B Talatahari","year":"2022","unstructured":"Talatahari B, Azizi M, Talatahari S, Tolouei M, Sareh P (2022) Crystal structure optimization approach to problem solving in mechanical engineering design. Multidiscip Model Mater Struct. https:\/\/doi.org\/10.1108\/mmms-10-2021-0174","journal-title":"Multidiscip Model Mater Struct"},{"issue":"May","key":"852_CR59","doi-asserted-by":"publisher","first-page":"107408","DOI":"10.1016\/j.cie.2021.107408","volume":"158","author":"B Abdollahzadeh","year":"2021","unstructured":"Abdollahzadeh B, Gharehchopogh FS, Mirjalili S (2021) African vultures optimization algorithm: a new nature-inspired metaheuristic algorithm for global optimization problems. Comput Ind Eng 158(May):107408. https:\/\/doi.org\/10.1016\/j.cie.2021.107408","journal-title":"Comput Ind Eng"},{"issue":"March","key":"852_CR60","doi-asserted-by":"publisher","first-page":"107224","DOI":"10.1016\/j.cie.2021.107224","volume":"156","author":"H Karami","year":"2021","unstructured":"Karami H, Anaraki MV, Farzin S, Mirjalili S (2021) Flow direction algorithm (FDA): a novel optimization approach for solving optimization problems. Comput Ind Eng 156(March):107224. https:\/\/doi.org\/10.1016\/j.cie.2021.107224","journal-title":"Comput Ind Eng"},{"key":"852_CR61","doi-asserted-by":"publisher","first-page":"3079","DOI":"10.1007\/s00366-020-00994-0","volume":"37","author":"S Barshandeh","year":"2021","unstructured":"Barshandeh S, Haghzadeh M (2021) A new hybrid chaotic atom search optimization based on tree-seed algorithm and Levy flight for solving optimization problems. Eng Comput 37:3079\u20133122. https:\/\/doi.org\/10.1007\/s00366-020-00994-0","journal-title":"Eng Comput"},{"key":"852_CR62","doi-asserted-by":"publisher","DOI":"10.1007\/s00366-021-01369-9","author":"B Abdollahzadeh","year":"2021","unstructured":"Abdollahzadeh B, Gharehchopogh FS (2021) A multi-objective optimization algorithm for feature selection problems. Eng Comput. https:\/\/doi.org\/10.1007\/s00366-021-01369-9","journal-title":"Eng Comput"},{"key":"852_CR63","doi-asserted-by":"publisher","first-page":"113609","DOI":"10.1016\/j.cma.2020.113609","volume":"376","author":"L Abualigah","year":"2021","unstructured":"Abualigah L, Diabat A, Mirjalili S, Elaziz MA, Gandomi AH (2021) The arithmetic optimization algorithm. Comput Methods Appl Mech Eng 376:113609. https:\/\/doi.org\/10.1016\/j.cma.2020.113609","journal-title":"Comput Methods Appl Mech Eng"},{"key":"852_CR64","doi-asserted-by":"publisher","first-page":"107250","DOI":"10.1016\/j.cie.2021.107250","volume":"157","author":"L Abualigah","year":"2021","unstructured":"Abualigah L, Yousri D, Elaziz MA, Ewees AA, Al-qaness MAA, Gandomi AH (2021) Aquila optimizer: a novel meta-heuristic optimization algorithm. Comput Ind Eng 157:107250. https:\/\/doi.org\/10.1016\/j.cie.2021.107250","journal-title":"Comput Ind Eng"},{"issue":"10","key":"852_CR65","doi-asserted-by":"publisher","first-page":"5887","DOI":"10.1002\/int.22535","volume":"36","author":"B Abdollahzadeh","year":"2021","unstructured":"Abdollahzadeh B, Gharehchopogh FS, Mirjalili S (2021) Artificial gorilla troops optimizer: a new nature-inspired metaheuristic algorithm for global optimization problems. Int J Intell Syst 36(10):5887\u20135958. https:\/\/doi.org\/10.1002\/int.22535","journal-title":"Int J Intell Syst"},{"key":"852_CR66","doi-asserted-by":"publisher","DOI":"10.1016\/j.cie.2020.107078","volume":"153","author":"M Abdel-Basset","year":"2021","unstructured":"Abdel-Basset M, Mohamed R, Chakrabortty RK, Ryan MJ, Mirjalili S (2021) An efficient binary slime mould algorithm integrated with a novel attacking-feeding strategy for feature selection. Comput Ind Eng 153:107078. https:\/\/doi.org\/10.1016\/j.cie.2020.107078","journal-title":"Comput Ind Eng"},{"key":"852_CR67","doi-asserted-by":"publisher","unstructured":"Marfia S, Vigliotti A (2021) 1D SMA models. In: Shape memory alloy engineering. Elsevier, pp 247\u2013290. https:\/\/doi.org\/10.1016\/B978-0-12-819264-1.00008-X","DOI":"10.1016\/B978-0-12-819264-1.00008-X"},{"issue":"1","key":"852_CR68","doi-asserted-by":"publisher","first-page":"151","DOI":"10.5152\/electrica.2021.20077","volume":"21","author":"D Izci","year":"2021","unstructured":"Izci D, Ekinci S (2021) Comparative performance analysis of slime mould algorithm for efficient design of proportional\u2013integral\u2013derivative controller. Electrica 21(1):151\u2013159. https:\/\/doi.org\/10.5152\/electrica.2021.20077","journal-title":"Electrica"},{"key":"852_CR69","unstructured":"Zitouni F, Harous S, Belkeram A, Hammou LEB (2021) The Archerfish hunting optimizer: a novel metaheuristic algorithm for global optimization. 178(1): 1\u201341. http:\/\/arxiv.org\/abs\/2102.02134"},{"issue":"March","key":"852_CR70","doi-asserted-by":"publisher","first-page":"380","DOI":"10.1016\/j.matcom.2020.09.027","volume":"181","author":"H Ren","year":"2021","unstructured":"Ren H, Li J, Chen H, Li CY (2021) Adaptive levy-assisted salp swarm algorithm: analysis and optimization case studies. Math Comput Simul 181(March):380\u2013409. https:\/\/doi.org\/10.1016\/j.matcom.2020.09.027","journal-title":"Math Comput Simul"},{"issue":"August 2020","key":"852_CR71","doi-asserted-by":"publisher","first-page":"113837","DOI":"10.1016\/j.eswa.2020.113837","volume":"165","author":"SW Lin","year":"2021","unstructured":"Lin SW, Cheng CY, Pourhejazy P, Ying KC (2021) Multi-temperature simulated annealing for optimizing mixed-blocking permutation flowshop scheduling problems. Expert Syst Appl 165(August 2020):113837. https:\/\/doi.org\/10.1016\/j.eswa.2020.113837","journal-title":"Expert Syst Appl"},{"issue":"November","key":"852_CR72","doi-asserted-by":"publisher","first-page":"188","DOI":"10.1016\/j.apm.2020.08.014","volume":"89","author":"R Salgotra","year":"2021","unstructured":"Salgotra R, Singh U, Singh S, Singh G, Mittal N (2021) Self-adaptive salp swarm algorithm for engineering optimization problems. Appl Math Model 89(November):188\u2013207. https:\/\/doi.org\/10.1016\/j.apm.2020.08.014","journal-title":"Appl Math Model"},{"key":"852_CR73","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2020.107713","author":"J Lee","year":"2020","unstructured":"Lee J, Perkins D (2020) A simulated annealing algorithm with a dual perturbation method for clustering. Pattern Recognit. https:\/\/doi.org\/10.1016\/j.patcog.2020.107713","journal-title":"Pattern Recognit"},{"issue":"2","key":"852_CR74","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"},{"issue":"1","key":"852_CR75","doi-asserted-by":"publisher","first-page":"49","DOI":"10.1007\/s12065-018-0187-8","volume":"12","author":"RM Rizk-Allah","year":"2019","unstructured":"Rizk-Allah RM, Hassanien AE (2019) A movable damped wave algorithm for solving global optimization problems. Evol Intell 12(1):49\u201372. https:\/\/doi.org\/10.1007\/s12065-018-0187-8","journal-title":"Evol Intell"},{"key":"852_CR76","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 (2019) Henry gas solubility optimization: a novel physics-based algorithm. Future Gener Comput Syst 101:646\u2013667. https:\/\/doi.org\/10.1016\/j.future.2019.07.015","journal-title":"Future Gener Comput Syst"},{"issue":"2","key":"852_CR77","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1007\/s12065-019-00212-x","volume":"12","author":"S Harifi","year":"2019","unstructured":"Harifi S, Khalilian M, Mohammadzadeh J, Ebrahimnejad S (2019) Emperor Penguins Colony: a new metaheuristic algorithm for optimization. Evol Intell 12(2):211\u2013226. https:\/\/doi.org\/10.1007\/s12065-019-00212-x","journal-title":"Evol Intell"},{"key":"852_CR78","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) \u201cHarris hawks optimization: algorithm and applications Harris hawks optimization. Algorithm Appl. https:\/\/doi.org\/10.1016\/j.future.2019.02.028","journal-title":"Algorithm Appl"},{"issue":"February","key":"852_CR79","doi-asserted-by":"publisher","first-page":"393","DOI":"10.1016\/j.engappai.2018.04.021","volume":"72","author":"A Cheraghalipour","year":"2018","unstructured":"Cheraghalipour A, Hajiaghaei-Keshteli M, Paydar MM (2018) Tree Growth Algorithm (TGA): a novel approach for solving optimization problems. Eng Appl Artif Intell 72(February):393\u2013414. https:\/\/doi.org\/10.1016\/j.engappai.2018.04.021","journal-title":"Eng Appl Artif Intell"},{"issue":"1","key":"852_CR80","doi-asserted-by":"publisher","first-page":"163","DOI":"10.1007\/s00521-016-2665-1","volume":"30","author":"WAHM Ghanem","year":"2018","unstructured":"Ghanem WAHM, Jantan A (2018) Hybridizing artificial bee colony with monarch butterfly optimization for numerical optimization problems. Neural Comput Appl 30(1):163\u2013181. https:\/\/doi.org\/10.1007\/s00521-016-2665-1","journal-title":"Neural Comput Appl"},{"key":"852_CR81","doi-asserted-by":"publisher","first-page":"14","DOI":"10.1007\/978-3-319-72550-5_2","volume":"700","author":"F Wahid","year":"2018","unstructured":"Wahid F, Ghazali R, Shah H (2018) An improved hybrid firefly algorithm for solving optimization problems. Adv Intell Syst Comput 700:14\u201323. https:\/\/doi.org\/10.1007\/978-3-319-72550-5_2","journal-title":"Adv Intell Syst Comput"},{"issue":"1","key":"852_CR82","doi-asserted-by":"publisher","first-page":"1079","DOI":"10.3233\/JIFS-16798","volume":"32","author":"S Arora","year":"2017","unstructured":"Arora S, Singh S (2017) An improved butterfly optimization algorithm with chaos. J Intell Fuzzy Syst 32(1):1079\u20131088. https:\/\/doi.org\/10.3233\/JIFS-16798","journal-title":"J Intell Fuzzy Syst"},{"key":"852_CR83","doi-asserted-by":"publisher","unstructured":"Shehab M, Khader AT, Al-Betar MA, Abualigah LM (2017) Hybridizing cuckoo search algorithm with hill climbing for numerical optimization problems. In: ICIT 2017\u20148th international conference information technology proceedings, no. May. pp 36\u201343. https:\/\/doi.org\/10.1109\/ICITECH.2017.8079912.","DOI":"10.1109\/ICITECH.2017.8079912"},{"issue":"6","key":"852_CR84","doi-asserted-by":"publisher","first-page":"1586","DOI":"10.1016\/j.jestch.2017.11.001","volume":"20","author":"N Singh","year":"2017","unstructured":"Singh N, Singh SB (2017) A novel hybrid GWO-SCA approach for optimization problems. Eng Sci Technol Int J 20(6):1586\u20131601. https:\/\/doi.org\/10.1016\/j.jestch.2017.11.001","journal-title":"Eng Sci Technol Int J"},{"key":"852_CR85","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2015.12.022","author":"S Mirjalili","year":"2016","unstructured":"Mirjalili S (2016) SCA: a sine cosine algorithm for solving optimization problems. Knowl Based Syst. https:\/\/doi.org\/10.1016\/j.knosys.2015.12.022","journal-title":"Knowl Based Syst"},{"issue":"1","key":"852_CR86","doi-asserted-by":"publisher","first-page":"24","DOI":"10.1016\/j.jcde.2015.06.003","volume":"3","author":"M Yazdani","year":"2016","unstructured":"Yazdani M, Jolai F (2016) Lion Optimization Algorithm (LOA): a nature-inspired metaheuristic algorithm. J Comput Des Eng 3(1):24\u201336. https:\/\/doi.org\/10.1016\/j.jcde.2015.06.003","journal-title":"J Comput Des Eng"},{"key":"852_CR87","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.compstruc.2016.03.001","volume":"169","author":"A Askarzadeh","year":"2016","unstructured":"Askarzadeh A (2016) A novel metaheuristic method for solving constrained engineering optimization problems: crow search algorithm. Comput Struct 169:1\u201312. https:\/\/doi.org\/10.1016\/j.compstruc.2016.03.001","journal-title":"Comput Struct"},{"key":"852_CR88","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.knosys.2014.07.025","volume":"75","author":"H Salimi","year":"2015","unstructured":"Salimi H (2015) Stochastic fractal search: a powerful metaheuristic algorithm. Knowl Based Syst 75:1\u201318. https:\/\/doi.org\/10.1016\/j.knosys.2014.07.025","journal-title":"Knowl Based Syst"},{"issue":"1","key":"852_CR89","doi-asserted-by":"publisher","first-page":"68","DOI":"10.14419\/jacst.v4i1.4094","volume":"4","author":"M Farahmandian","year":"2015","unstructured":"Farahmandian M, Hatamlou A (2015) Solving optimization problems using black hole algorithm. J Adv Comput Sci Technol 4(1):68. https:\/\/doi.org\/10.14419\/jacst.v4i1.4094","journal-title":"J Adv Comput Sci Technol"},{"issue":"15","key":"852_CR90","doi-asserted-by":"publisher","first-page":"6676","DOI":"10.1016\/j.eswa.2014.05.009","volume":"41","author":"M Ghaemi","year":"2014","unstructured":"Ghaemi M, Feizi-Derakhshi MR (2014) Forest optimization algorithm. Expert Syst Appl 41(15):6676\u20136687. https:\/\/doi.org\/10.1016\/j.eswa.2014.05.009","journal-title":"Expert Syst Appl"},{"issue":"12","key":"852_CR91","doi-asserted-by":"publisher","first-page":"10","DOI":"10.5815\/ijmecs.2013.12.02","volume":"5","author":"S Roy","year":"2013","unstructured":"Roy S, Chaudhuri SS (2013) Cuckoo search algorithm using L\u00e8vy flight: a review. Int J Mod Educ Comput Sci 5(12):10\u201315. https:\/\/doi.org\/10.5815\/ijmecs.2013.12.02","journal-title":"Int J Mod Educ Comput Sci"},{"issue":"1","key":"852_CR92","doi-asserted-by":"publisher","first-page":"36","DOI":"10.1504\/ijsi.2013.055801","volume":"1","author":"XS Yang","year":"2013","unstructured":"Yang XS, He X (2013) Firefly algorithm: recent advances and applications. Int J Swarm Intell 1(1):36. https:\/\/doi.org\/10.1504\/ijsi.2013.055801","journal-title":"Int J Swarm Intell"},{"issue":"3","key":"852_CR93","doi-asserted-by":"publisher","first-page":"141","DOI":"10.1504\/IJBIC.2013.055093","volume":"5","author":"XS Yang","year":"2013","unstructured":"Yang XS (2013) Bat algorithm: literature review and applications. Int J Bioinspired Comput 5(3):141\u2013149. https:\/\/doi.org\/10.1504\/IJBIC.2013.055093","journal-title":"Int J Bioinspired Comput"},{"key":"852_CR94","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-38577-3","author":"Y Gheraibia","year":"2013","unstructured":"Gheraibia Y, Moussaoui A (2013) Recent trends. Appl Artif Intell. https:\/\/doi.org\/10.1007\/978-3-642-38577-3","journal-title":"Appl Artif Intell"},{"issue":"12","key":"852_CR95","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":"852_CR96","doi-asserted-by":"publisher","unstructured":"Y X-s (2012) Flower pollination algorithm for global optimization. In: Unconventional computation and natural computation. Springer, p 2409. https:\/\/doi.org\/10.1007\/978-3-642-32894-7_27","DOI":"10.1007\/978-3-642-32894-7_27"},{"issue":"1","key":"852_CR97","doi-asserted-by":"publisher","first-page":"397","DOI":"10.1007\/978-81-322-0487-9_38","volume":"130","author":"A Ghodrati","year":"2012","unstructured":"Ghodrati A, Lotfi S (2012) A hybrid CS\/GA algorithm for global optimization. Adv Intell Soft Comput 130(1):397\u2013404. https:\/\/doi.org\/10.1007\/978-81-322-0487-9_38","journal-title":"Adv Intell Soft Comput"},{"issue":"2","key":"852_CR98","doi-asserted-by":"publisher","first-page":"60","DOI":"10.1177\/003754970107600201","volume":"76","author":"ZW Geem","year":"2001","unstructured":"Geem ZW, Kim JH, Loganathan GV (2001) A new heuristic optimization algorithm: harmony search. SIMULATION 76(2):60\u201368. https:\/\/doi.org\/10.1177\/003754970107600201","journal-title":"SIMULATION"},{"key":"852_CR99","doi-asserted-by":"publisher","DOI":"10.1023\/A:1008202821328","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 Glob Optim. https:\/\/doi.org\/10.1023\/A:1008202821328","journal-title":"J Glob Optim"},{"issue":"3","key":"852_CR100","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\u2014part I. Orsa J Comput 1(3):190\u2013206. https:\/\/doi.org\/10.1287\/ijoc.1.3.190","journal-title":"Orsa J Comput"},{"issue":"7\u20138","key":"852_CR101","doi-asserted-by":"publisher","first-page":"1867","DOI":"10.1007\/s00521-013-1433-8","volume":"24","author":"X Li","year":"2014","unstructured":"Li X, Zhang J, Yin M (2014) Animal migration optimization: an optimization algorithm inspired by animal migration behavior. Neural Comput Appl 24(7\u20138):1867\u20131877. https:\/\/doi.org\/10.1007\/s00521-013-1433-8","journal-title":"Neural Comput Appl"},{"key":"852_CR102","doi-asserted-by":"publisher","first-page":"120","DOI":"10.1016\/j.knosys.2015.12.022","volume":"96","author":"S Mirjalili","year":"2016","unstructured":"Mirjalili S (2016) SCA: a sine cosine algorithm for solving optimization problems. Knowl Based Syst 96:120\u2013133. https:\/\/doi.org\/10.1016\/j.knosys.2015.12.022","journal-title":"Knowl Based Syst"},{"issue":"5","key":"852_CR103","doi-asserted-by":"publisher","first-page":"973","DOI":"10.1109\/TEVC.2009.2011992","volume":"13","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 13(5):973\u2013990. https:\/\/doi.org\/10.1109\/TEVC.2009.2011992","journal-title":"IEEE Trans Evol Comput"},{"key":"852_CR104","doi-asserted-by":"publisher","DOI":"10.1016\/j.isatra.2014.03.018","author":"AH Gandomi","year":"2014","unstructured":"Gandomi AH (2014) Interior search algorithm (ISA): a novel approach for global optimization. ISA Trans. https:\/\/doi.org\/10.1016\/j.isatra.2014.03.018","journal-title":"ISA Trans"},{"key":"852_CR105","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.compchemeng.2017.01.046","volume":"103","author":"A Tabari","year":"2017","unstructured":"Tabari A, Ahmad A (2017) A new optimization method: electro-search algorithm. Comput Chem Eng 103:1\u201311. https:\/\/doi.org\/10.1016\/j.compchemeng.2017.01.046","journal-title":"Comput Chem Eng"},{"key":"852_CR106","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":"852_CR107","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2020.113282","author":"Z Xu","year":"2020","unstructured":"Xu Z et al (2020) Orthogonally-designed adapted grasshopper optimization: a comprehensive analysis. Expert Syst Appl. https:\/\/doi.org\/10.1016\/j.eswa.2020.113282","journal-title":"Expert Syst Appl"},{"key":"852_CR108","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":"11","key":"852_CR109","doi-asserted-by":"publisher","first-page":"3926","DOI":"10.1007\/s10489-020-01727-y","volume":"50","author":"MH Qais","year":"2020","unstructured":"Qais MH, Hasanien HM, Alghuwainem S (2020) Transient search optimization: a new meta-heuristic optimization algorithm. Appl Intell 50(11):3926\u20133941. https:\/\/doi.org\/10.1007\/s10489-020-01727-y","journal-title":"Appl Intell"},{"key":"852_CR110","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":"852_CR111","doi-asserted-by":"publisher","DOI":"10.1016\/j.swevo.2015.07.002","author":"H Abedinpourshotorban","year":"2015","unstructured":"Abedinpourshotorban H, Mariyam S, Beheshti Z (2015) Electromagnetic field optimization: a physics-inspired metaheuristic optimization algorithm. Swarm Evol Comput. https:\/\/doi.org\/10.1016\/j.swevo.2015.07.002","journal-title":"Swarm Evol Comput"},{"key":"852_CR112","doi-asserted-by":"publisher","first-page":"103300","DOI":"10.1016\/j.engappai.2019.103300","volume":"87","author":"W Zhao","year":"2020","unstructured":"Zhao W, Zhang Z, Wang L (2020) Manta ray foraging optimization: an effective bio-inspired optimizer for engineering applications. Eng Appl Artif Intell 87:103300. https:\/\/doi.org\/10.1016\/j.engappai.2019.103300","journal-title":"Eng Appl Artif Intell"},{"issue":"12","key":"852_CR113","doi-asserted-by":"publisher","first-page":"9121","DOI":"10.1007\/s00500-019-04443-z","volume":"24","author":"A Khatri","year":"2020","unstructured":"Khatri A, Gaba A, Rana KPS, Kumar V (2020) A novel life choice-based optimizer. Soft Comput 24(12):9121\u20139141. https:\/\/doi.org\/10.1007\/s00500-019-04443-z","journal-title":"Soft Comput"},{"key":"852_CR114","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"},{"issue":"1","key":"852_CR115","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":"852_CR116","doi-asserted-by":"publisher","unstructured":"Banerjee N, Mukhopadhyay S (2019) HC-PSOGWO: hybrid crossover oriented PSO and GWO based co-evolution for global optimization. In: Proceedings of 2019 IEEE Reg. 10 Symposium TENSYMP 2019, vol 7, pp 162\u2013167. https:\/\/doi.org\/10.1109\/TENSYMP46218.2019.8971231.","DOI":"10.1109\/TENSYMP46218.2019.8971231"},{"key":"852_CR117","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"},{"issue":"1","key":"852_CR118","doi-asserted-by":"publisher","first-page":"641","DOI":"10.1007\/s00366-019-00846-6","volume":"37","author":"GG Tejani","year":"2021","unstructured":"Tejani GG, Kumar S, Gandomi AH (2021) Multi-objective heat transfer search algorithm for truss optimization. Eng Comput 37(1):641\u2013662. https:\/\/doi.org\/10.1007\/s00366-019-00846-6","journal-title":"Eng Comput"},{"key":"852_CR119","doi-asserted-by":"publisher","DOI":"10.1007\/s00366-021-01487-4","author":"D Dhawale","year":"2021","unstructured":"Dhawale D, Kamboj VK, Anand P (2021) An improved chaotic Harris Hawks optimizer for solving numerical and engineering optimization problems. Eng Comput. https:\/\/doi.org\/10.1007\/s00366-021-01487-4","journal-title":"Eng Comput"},{"key":"852_CR120","doi-asserted-by":"publisher","DOI":"10.1007\/s11227-021-04105-8","author":"S Chauhan","year":"2021","unstructured":"Chauhan S, Vashishtha G, Kumar A (2021) A symbiosis of arithmetic optimizer with slime mould algorithm for improving global optimization and conventional design problem. J Supercomput. https:\/\/doi.org\/10.1007\/s11227-021-04105-8","journal-title":"J Supercomput"},{"key":"852_CR121","doi-asserted-by":"publisher","DOI":"10.1007\/s12652-021-03372-w","author":"L Abualigah","year":"2021","unstructured":"Abualigah L, Diabat A, Elaziz MA (2021) Improved slime mould algorithm by opposition-based learning and Levy flight distribution for global optimization and advances in real-world engineering problems. J Ambient Intell Humaniz Comput. https:\/\/doi.org\/10.1007\/s12652-021-03372-w","journal-title":"J Ambient Intell Humaniz Comput"},{"key":"852_CR122","doi-asserted-by":"publisher","DOI":"10.1155\/2021\/6379469","author":"S Wang","year":"2021","unstructured":"Wang S et al (2021) A hybrid SSA and SMA with mutation opposition-based learning for constrained engineering problems. Comput Intell Neurosci. https:\/\/doi.org\/10.1155\/2021\/6379469","journal-title":"Comput Intell Neurosci"},{"key":"852_CR123","doi-asserted-by":"publisher","unstructured":"M. K. Naik, R. Panda, and A. Abraham, \u201cNormalized square difference based multilevel thresholding technique for multispectral images using leader slime mould algorithm,\u201d J. King Saud Univ. - Comput. Inf. Sci., no. xxxx, 2020, doi: https:\/\/doi.org\/10.1016\/j.jksuci.2020.10.030.","DOI":"10.1016\/j.jksuci.2020.10.030"},{"key":"852_CR124","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2021.107632","volume":"110","author":"M Salama","year":"2021","unstructured":"Salama M, Srinivas S (2021) Adaptive neighborhood simulated annealing for sustainability-oriented single machine scheduling with deterioration effect. Appl Soft Comput 110:107632. https:\/\/doi.org\/10.1016\/j.asoc.2021.107632","journal-title":"Appl Soft Comput"},{"key":"852_CR125","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2021.107698","volume":"111","author":"R Bandyopadhyay","year":"2021","unstructured":"Bandyopadhyay R, Basu A, Cuevas E, Sarkar R (2021) Harris Hawks optimisation with simulated annealing as a deep feature selection method for screening of COVID-19 CT-scans. Appl Soft Comput 111:107698. https:\/\/doi.org\/10.1016\/j.asoc.2021.107698","journal-title":"Appl Soft Comput"},{"key":"852_CR126","doi-asserted-by":"publisher","first-page":"100911","DOI":"10.1016\/j.swevo.2021.100911","volume":"64","author":"\u0130 Ilhan","year":"2021","unstructured":"Ilhan \u0130 (2021) An improved simulated annealing algorithm with crossover operator for capacitated vehicle routing problem. Swarm Evol Comput 64:100911. https:\/\/doi.org\/10.1016\/j.swevo.2021.100911","journal-title":"Swarm Evol Comput"},{"key":"852_CR127","doi-asserted-by":"publisher","first-page":"167","DOI":"10.1007\/978-3-030-58930-1_11","volume-title":"Heuristics for optimization and learning","author":"M Lalaoui","year":"2021","unstructured":"Lalaoui M, El Afia A, Chiheb R (2021) Dynamic simulated annealing with adaptive neighborhood using Hidden Markov Model. In: Yalaoui F, Amodeo L, Talbi E-G (eds) Heuristics for optimization and learning. Springer International Publishing, Cham, pp 167\u2013182. https:\/\/doi.org\/10.1007\/978-3-030-58930-1_11"},{"key":"852_CR128","doi-asserted-by":"publisher","DOI":"10.1007\/s13369-021-06383-z","author":"D Izci","year":"2022","unstructured":"Izci D, Ekinci S, Hekimo\u011flu B (2022) Fractional-order PID controller design for buck converter system via hybrid L\u00e8vy flight distribution and simulated annealing algorithm. Arab J Sci Eng. https:\/\/doi.org\/10.1007\/s13369-021-06383-z","journal-title":"Arab J Sci Eng"},{"key":"852_CR129","doi-asserted-by":"publisher","DOI":"10.1007\/s12065-021-00615-9","author":"D Izci","year":"2021","unstructured":"Izci D (2021) A novel improved atom search optimization algorithm for designing power system stabilizer. Evol Intell. https:\/\/doi.org\/10.1007\/s12065-021-00615-9","journal-title":"Evol Intell"},{"issue":"4","key":"852_CR130","doi-asserted-by":"publisher","first-page":"3889","DOI":"10.1007\/s13369-020-05228-5","volume":"46","author":"E Eker","year":"2021","unstructured":"Eker E, Kayri M, Ekinci S, Izci D (2021) A new fusion of ASO with SA algorithm and its applications to MLP training and DC motor speed control. Arab J Sci Eng 46(4):3889\u20133911. https:\/\/doi.org\/10.1007\/s13369-020-05228-5","journal-title":"Arab J Sci Eng"},{"issue":"2","key":"852_CR131","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":"852_CR132","doi-asserted-by":"publisher","DOI":"10.1016\/b978-0-12-049601-3.50010-9","author":"D Kessler","year":"1982","unstructured":"Kessler D (1982) Plasmodial structure and motility. Cell Biol Physarum Didymium. https:\/\/doi.org\/10.1016\/b978-0-12-049601-3.50010-9","journal-title":"Cell Biol Physarum Didymium"},{"key":"852_CR133","doi-asserted-by":"publisher","unstructured":"Camp AWG, Bulletin S, Botanical T, Apr N (2016) Torrey botanical society a method of cultivating myxomycete plasmodia. 63(4): 205\u2013210 https:\/\/doi.org\/10.2307\/2480903","DOI":"10.2307\/2480903"},{"issue":"2","key":"852_CR134","doi-asserted-by":"publisher","first-page":"49","DOI":"10.1007\/BF02872461","volume":"9","author":"W Seifriz","year":"1943","unstructured":"Seifriz W (1943) Protoplasmic streaming. Bot Rev 9(2):49\u2013123. https:\/\/doi.org\/10.1007\/BF02872461","journal-title":"Bot Rev"},{"issue":"3","key":"852_CR135","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. https:\/\/doi.org\/10.1016\/S0301-4622(00)00108-3","journal-title":"Biophys Chem"},{"key":"852_CR136","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. https:\/\/doi.org\/10.1016\/j.swevo.2016.03.002","journal-title":"Swarm Evol Comput"},{"issue":"23","key":"852_CR137","doi-asserted-by":"publisher","first-page":"3734","DOI":"10.1016\/j.jmb.2015.07.007","volume":"427","author":"M Beekman","year":"2015","unstructured":"Beekman M, Latty T (2015) Brainless but multi-headed: decision making by the acellular slime mould Physarum polycephalum. J Mol Biol 427(23):3734\u20133743. https:\/\/doi.org\/10.1016\/j.jmb.2015.07.007","journal-title":"J Mol Biol"},{"issue":"1","key":"852_CR138","doi-asserted-by":"publisher","first-page":"22","DOI":"10.1890\/09-0358.1","volume":"91","author":"T Latty","year":"2010","unstructured":"Latty T, Beekman M (2010) Food quality and the risk of light exposure affect patch-choice decisions in the slime mould Physarum polycephalum. Ecol Ecol Soc Am 91(1):22\u201327. https:\/\/doi.org\/10.1890\/09-0358.1","journal-title":"Ecol Ecol Soc Am"},{"issue":"1705","key":"852_CR139","doi-asserted-by":"publisher","first-page":"539","DOI":"10.1098\/rspb.2010.1624","volume":"278","author":"T Latty","year":"2011","unstructured":"Latty T, Beekman M (2011) Speed-accuracy trade-offs during foraging decisions in the acellular slime mould Physarum polycephalum. Proc R Soc B Biol Sci 278(1705):539\u2013545. https:\/\/doi.org\/10.1098\/rspb.2010.1624","journal-title":"Proc R Soc B Biol Sci"},{"issue":"8","key":"852_CR140","doi-asserted-by":"publisher","first-page":"1175","DOI":"10.1242\/jeb.116533","volume":"218","author":"T Latty","year":"2015","unstructured":"Latty T, Beekman M (2015) Slime moulds use heuristics based on within-patch experience to decide when to leave. J Exp Biol 218(8):1175\u20131179. https:\/\/doi.org\/10.1242\/jeb.116533","journal-title":"J Exp Biol"},{"issue":"2","key":"852_CR141","doi-asserted-by":"publisher","first-page":"318","DOI":"10.1126\/science.26.678.918","volume":"130","author":"WC Johnson","year":"1948","unstructured":"Johnson WC (1948) The university of Chicago. J Chem Educ 130(2):318\u2013321. https:\/\/doi.org\/10.1126\/science.26.678.918","journal-title":"J Chem Educ"},{"issue":"6","key":"852_CR142","doi-asserted-by":"publisher","first-page":"1160","DOI":"10.1093\/beheco\/arp111","volume":"20","author":"T Latty","year":"2009","unstructured":"Latty T, Beekman M (2009) Food quality affects search strategy in the acellular slime mould, Physarum polycephalum. Behav Ecol 20(6):1160\u20131167. https:\/\/doi.org\/10.1093\/beheco\/arp111","journal-title":"Behav Ecol"},{"issue":"4","key":"852_CR143","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":"852_CR144","doi-asserted-by":"publisher","first-page":"315","DOI":"10.1016\/j.asoc.2015.07.028","volume":"36","author":"H Shareef","year":"2015","unstructured":"Shareef H, Ibrahim AA, Mutlag AH (2015) Lightning search algorithm. Appl Soft Comput J 36:315\u2013333. https:\/\/doi.org\/10.1016\/j.asoc.2015.07.028","journal-title":"Appl Soft Comput J"},{"key":"852_CR145","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-020-05004-4","author":"TR Farshi","year":"2020","unstructured":"Farshi TR (2020) Battle royale optimization algorithm. Neural Comput Appl. https:\/\/doi.org\/10.1007\/s00521-020-05004-4","journal-title":"Neural Comput Appl"},{"issue":"4","key":"852_CR146","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"},{"issue":"3","key":"852_CR147","doi-asserted-by":"publisher","first-page":"458","DOI":"10.18178\/ijmlc.2020.10.3.957","volume":"10","author":"R Hans","year":"2020","unstructured":"Hans R, Kaur H (2020) Opposition-based enhanced grey wolf optimization algorithm for feature selection in breast density classification. Int J Mach Learn Comput 10(3):458\u2013464. https:\/\/doi.org\/10.18178\/ijmlc.2020.10.3.957","journal-title":"Int J Mach Learn Comput"},{"key":"852_CR148","doi-asserted-by":"publisher","first-page":"163","DOI":"10.1016\/j.advengsoft.2017.07.002","volume":"114","author":"S Mirjalili","year":"2017","unstructured":"Mirjalili S, Gandomi AH, Mirjalili SZ, Saremi S, Faris H, Mirjalili SM (2017) Salp Swarm Algorithm: a bio-inspired optimizer for engineering design problems. Adv Eng Softw 114:163\u2013191. https:\/\/doi.org\/10.1016\/j.advengsoft.2017.07.002","journal-title":"Adv Eng Softw"},{"key":"852_CR149","doi-asserted-by":"publisher","unstructured":"Mirjalili SMSSM, Lewis A (2014) Grey wolf optimizer 69. https:\/\/doi.org\/10.1016\/j.advengsoft.2013.12.007","DOI":"10.1016\/j.advengsoft.2013.12.007"},{"key":"852_CR150","doi-asserted-by":"publisher","first-page":"11957","DOI":"10.1007\/s00500-019-04640-w","volume":"24","author":"AK Bhullar","year":"2020","unstructured":"Bhullar AK, Kaur R, Sondhi S (2020) Enhanced crow search algorithm for AVR optimization. Soft Comput 24:11957\u201311987. https:\/\/doi.org\/10.1007\/s00500-019-04640-w","journal-title":"Soft Comput"},{"issue":"11","key":"852_CR151","doi-asserted-by":"publisher","first-page":"1437","DOI":"10.1016\/j.pnsc.2008.03.029","volume":"18","author":"J Wang","year":"2008","unstructured":"Wang J, Wang D (2008) Particle swarm optimization with a leader and followers. Prog Nat Sci 18(11):1437\u20131443. https:\/\/doi.org\/10.1016\/j.pnsc.2008.03.029","journal-title":"Prog Nat Sci"},{"key":"852_CR152","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"},{"issue":"5","key":"852_CR153","doi-asserted-by":"publisher","first-page":"2592","DOI":"10.1016\/j.asoc.2012.11.026","volume":"13","author":"A Sadollah","year":"2013","unstructured":"Sadollah A, Bahreininejad A, Eskandar H, Hamdi M (2013) Mine blast algorithm: a new population based algorithm for solving constrained engineering optimization problems. Appl Soft Comput 13(5):2592\u20132612. https:\/\/doi.org\/10.1016\/j.asoc.2012.11.026","journal-title":"Appl Soft Comput"},{"key":"852_CR154","doi-asserted-by":"publisher","first-page":"250","DOI":"10.1016\/j.ins.2020.02.013","volume":"520","author":"T Le-Duc","year":"2020","unstructured":"Le-Duc T, Nguyen QH, Nguyen-Xuan H (2020) Balancing composite motion optimization. Inf Sci (Ny) 520:250\u2013270. https:\/\/doi.org\/10.1016\/j.ins.2020.02.013","journal-title":"Inf Sci (Ny)"},{"issue":"2","key":"852_CR155","doi-asserted-by":"publisher","first-page":"1676","DOI":"10.1016\/j.eswa.2009.06.044","volume":"37","author":"LS dos Coelho","year":"2010","unstructured":"dos Coelho LS (2010) Gaussian quantum-behaved particle swarm optimization approaches for constrained engineering design problems. Expert Syst Appl 37(2):1676\u20131683. https:\/\/doi.org\/10.1016\/j.eswa.2009.06.044","journal-title":"Expert Syst Appl"},{"key":"852_CR156","doi-asserted-by":"publisher","DOI":"10.1108\/02644401011008577","author":"A Kaveh","year":"2010","unstructured":"Kaveh A, Talatahari S (2010) An improved ant colony optimization for constrained engineering design problems. Eng Comput (Swansea, Wales). https:\/\/doi.org\/10.1108\/02644401011008577","journal-title":"Eng Comput (Swansea, Wales)"},{"issue":"1","key":"852_CR157","doi-asserted-by":"publisher","first-page":"340","DOI":"10.1016\/j.amc.2006.07.105","volume":"186","author":"F Huang","year":"2007","unstructured":"Huang F, Wang L, He Q (2007) An effective co-evolutionary differential evolution for constrained optimization. Appl Math Comput 186(1):340\u2013356. https:\/\/doi.org\/10.1016\/j.amc.2006.07.105","journal-title":"Appl Math Comput"},{"key":"852_CR158","doi-asserted-by":"publisher","unstructured":"Bernardino HS, Barbosa HJC, Lemonge ACC (2007) A hybrid genetic algorithm for constrained optimization problems in mechanical engineering. 2007 IEEE Congr. Evol. Comput. CEC 2007, no. September, pp 646\u2013653. https:\/\/doi.org\/10.1109\/CEC.2007.4424532","DOI":"10.1109\/CEC.2007.4424532"},{"issue":"6","key":"852_CR159","doi-asserted-by":"publisher","first-page":"947","DOI":"10.1007\/s00158-009-0454-5","volume":"41","author":"L Wang","year":"2010","unstructured":"Wang L, Li LP (2010) An effective differential evolution with level comparison for constrained engineering design. Struct Multidiscip Optim 41(6):947\u2013963. https:\/\/doi.org\/10.1007\/s00158-009-0454-5","journal-title":"Struct Multidiscip Optim"},{"key":"852_CR160","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: SiC-PSO. Eng Optim 32:319\u2013326","journal-title":"Eng Optim"},{"issue":"3","key":"852_CR161","doi-asserted-by":"publisher","first-page":"193","DOI":"10.1016\/S1474-0346(02)00011-3","volume":"16","author":"C Ac Coello","year":"2002","unstructured":"Ac Coello C, Montes EM (2002) Constraint-handling in genetic algorithms through the use of dominance-based tournament selection. Adv Eng Inform 16(3):193\u2013203. https:\/\/doi.org\/10.1016\/S1474-0346(02)00011-3","journal-title":"Adv Eng Inform"},{"issue":"6","key":"852_CR162","doi-asserted-by":"publisher","first-page":"832","DOI":"10.1080\/18756891.2010.9727745","volume":"3","author":"L Gao","year":"2010","unstructured":"Gao L, Hailu A (2010) Comprehensive learning particle swarm optimizer for constrained mixed-variable optimization problems. Int J Comput Intell Syst 3(6):832\u2013842. https:\/\/doi.org\/10.1080\/18756891.2010.9727745","journal-title":"Int J Comput Intell Syst"},{"key":"852_CR163","unstructured":"Deb K, Goyal M (1996) A combined genetic adaptive search (GeneAS) for engineering design. Comput Sci Inform 26(1): 30\u201345. http:\/\/citeseerx.ist.psu.edu\/viewdoc\/summary,doi=10.1.1.27.767%5Cnhttp:\/\/repository.ias.ac.in\/82723\/"},{"issue":"1","key":"852_CR164","doi-asserted-by":"publisher","first-page":"51","DOI":"10.1016\/J.EPSR.2003.12.017","volume":"71","author":"TAA Victoire","year":"2004","unstructured":"Victoire TAA, Jeyakumar AE (2004) Hybrid PSO\u2013SQP for economic dispatch with valve-point effect. Electr Power Syst Res 71(1):51\u201359. https:\/\/doi.org\/10.1016\/J.EPSR.2003.12.017","journal-title":"Electr Power Syst Res"},{"key":"852_CR165","doi-asserted-by":"publisher","unstructured":"Yalcinoz T, Altun H, Uzam M (2001) Economic dispatch solution using a genetic algorithm based on arithmetic crossover. 2001 IEEE Porto Power Tech Proc, vol 2(4): 153\u2013156. https:\/\/doi.org\/10.1109\/PTC.2001.964734.","DOI":"10.1109\/PTC.2001.964734"},{"issue":"4","key":"852_CR166","doi-asserted-by":"publisher","first-page":"386","DOI":"10.1109\/TEVC.2003.814902","volume":"7","author":"T Ray","year":"2003","unstructured":"Ray T, Liew KM (2003) Society and civilization: an optimization algorithm based on the simulation of social behavior. IEEE Trans Evol Comput 7(4):386\u2013396. https:\/\/doi.org\/10.1109\/TEVC.2003.814902","journal-title":"IEEE Trans Evol Comput"},{"key":"852_CR167","doi-asserted-by":"publisher","first-page":"143","DOI":"10.1007\/978-981-10-5221-7_14","volume":"720","author":"B Zolghadr-Asli","year":"2018","unstructured":"Zolghadr-Asli B, Bozorg-Haddad O, Chu X (2018) Crow search algorithm (CSA). Stud Comput Intell 720:143\u2013149. https:\/\/doi.org\/10.1007\/978-981-10-5221-7_14","journal-title":"Stud Comput Intell"},{"issue":"6","key":"852_CR168","doi-asserted-by":"publisher","first-page":"735","DOI":"10.1080\/03052150108940941","volume":"33","author":"T Ray","year":"2001","unstructured":"Ray T, Saini P (2001) Engineering design optimization using a swarm with an intelligent information sharing among individuals. Eng Optim 33(6):735\u2013748. https:\/\/doi.org\/10.1080\/03052150108940941","journal-title":"Eng Optim"},{"issue":"2","key":"852_CR169","doi-asserted-by":"publisher","first-page":"327","DOI":"10.1016\/j.cnsns.2012.07.017","volume":"18","author":"AH Gandomi","year":"2013","unstructured":"Gandomi AH, Yun GJ, Yang XS, Talatahari S (2013) Chaos-enhanced accelerated particle swarm optimization. Commun Nonlinear Sci Numer Simul 18(2):327\u2013340. https:\/\/doi.org\/10.1016\/j.cnsns.2012.07.017","journal-title":"Commun Nonlinear Sci Numer Simul"},{"key":"852_CR170","doi-asserted-by":"publisher","first-page":"106734","DOI":"10.1016\/j.asoc.2020.106734","volume":"98","author":"Z Feng","year":"2021","unstructured":"Feng Z, Niu W, Liu S (2021) Cooperation search algorithm: a novel metaheuristic evolutionary intelligence algorithm for numerical optimization and engineering optimization problems. Appl Soft Comput 98:106734. https:\/\/doi.org\/10.1016\/j.asoc.2020.106734","journal-title":"Appl Soft Comput"},{"key":"852_CR171","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-020-05229-3","author":"A Bhadoria","year":"2020","unstructured":"Bhadoria A, Marwaha S, Kamboj VK (2020) A solution to statistical and multidisciplinary design optimization problems using hGWO-SA algorithm. Neural Comput Appl. https:\/\/doi.org\/10.1007\/s00521-020-05229-3","journal-title":"Neural Comput Appl"},{"issue":"15","key":"852_CR172","doi-asserted-by":"publisher","first-page":"3043","DOI":"10.1016\/j.ins.2008.02.014","volume":"178","author":"M Zhang","year":"2008","unstructured":"Zhang M, Luo W, Wang X (2008) Differential evolution with dynamic stochastic selection for constrained optimization. Inf Sci (Ny) 178(15):3043\u20133074. https:\/\/doi.org\/10.1016\/j.ins.2008.02.014","journal-title":"Inf Sci (Ny)"},{"key":"852_CR173","doi-asserted-by":"publisher","DOI":"10.1007\/s10489-018-1325-9","author":"A Bhadoria","year":"2018","unstructured":"Bhadoria A, Kamboj VK (2018) Optimal generation scheduling and dispatch of thermal generating units considering impact of wind penetration using hGWO-RES algorithm. Appl Intell. https:\/\/doi.org\/10.1007\/s10489-018-1325-9","journal-title":"Appl Intell"},{"issue":"4\u20136","key":"852_CR174","doi-asserted-by":"publisher","first-page":"803","DOI":"10.1016\/j.cma.2006.06.010","volume":"196","author":"GG Dimopoulos","year":"2007","unstructured":"Dimopoulos GG (2007) Mixed-variable engineering optimization based on evolutionary and social metaphors. Comput Methods Appl Mech Eng 196(4\u20136):803\u2013817. https:\/\/doi.org\/10.1016\/j.cma.2006.06.010","journal-title":"Comput Methods Appl Mech Eng"},{"issue":"23\u201324","key":"852_CR175","doi-asserted-by":"publisher","first-page":"2325","DOI":"10.1016\/j.compstruc.2011.08.002","volume":"89","author":"AH Gandomi","year":"2011","unstructured":"Gandomi AH, Yang XS, Alavi AH (2011) Mixed variable structural optimization using Firefly Algorithm. Comput Struct 89(23\u201324):2325\u20132336. https:\/\/doi.org\/10.1016\/j.compstruc.2011.08.002","journal-title":"Comput Struct"},{"key":"852_CR176","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2019.105277","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. Knowl Based Syst. https:\/\/doi.org\/10.1016\/j.knosys.2019.105277","journal-title":"Knowl Based Syst"},{"issue":"2","key":"852_CR177","doi-asserted-by":"publisher","first-page":"125","DOI":"10.1080\/03052159808941241","volume":"30","author":"VV Litinetski","year":"1998","unstructured":"Litinetski VV, Abramzon BM (1998) Mars\u2014a multistart adaptive random search method for global constrained optimization in engineering applications. Eng Optim 30(2):125\u2013154. https:\/\/doi.org\/10.1080\/03052159808941241","journal-title":"Eng Optim"},{"issue":"4","key":"852_CR178","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"},{"key":"852_CR179","unstructured":"Yun Y (2005) Study on adaptive hybrid genetic algorithm and its applications to engineering design problems no. January"},{"issue":"4","key":"852_CR180","doi-asserted-by":"publisher","first-page":"277","DOI":"10.1080\/03052159308940980","volume":"21","author":"C Zhang","year":"1993","unstructured":"Zhang C, Wang HP (1993) Mixed-discrete nonlinear optimization with simulated annealing. Eng Optim 21(4):277\u2013291. https:\/\/doi.org\/10.1080\/03052159308940980","journal-title":"Eng Optim"},{"issue":"2","key":"852_CR181","doi-asserted-by":"publisher","first-page":"223","DOI":"10.1115\/1.2912596","volume":"112","author":"E Sandgren","year":"1990","unstructured":"Sandgren E (1990) Nonlinear integer and discrete programming in mechanical design optimization. J Mech Des Trans ASME 112(2):223\u2013229. https:\/\/doi.org\/10.1115\/1.2912596","journal-title":"J Mech Des Trans ASME"},{"issue":"4","key":"852_CR182","doi-asserted-by":"publisher","first-page":"263","DOI":"10.1080\/03052159108941075","volume":"17","author":"JF Fu","year":"1991","unstructured":"Fu JF, Fenton RG, Cleghorn WL (1991) A mixed integer-discrete-continuous programming method and its application to engineering design optimization. Eng Optim 17(4):263\u2013280. https:\/\/doi.org\/10.1080\/03052159108941075","journal-title":"Eng Optim"},{"key":"852_CR183","doi-asserted-by":"publisher","DOI":"10.1002\/(sici)1097-0207(19960315)39:5<829::aid-nme884>3.0.co;2-u","author":"H Chlckermane","year":"1996","unstructured":"Chlckermane H, Gea HC (1996) Structural optimization using a new local approximation method. Int J Numer Methods Eng. https:\/\/doi.org\/10.1002\/(sici)1097-0207(19960315)39:5%3c829::aid-nme884%3e3.0.co;2-u","journal-title":"Int J Numer Methods Eng"},{"issue":"1","key":"852_CR184","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":"852_CR185","doi-asserted-by":"publisher","first-page":"98","DOI":"10.1016\/j.compstruc.2014.03.007","volume":"139","author":"MY Cheng","year":"2014","unstructured":"Cheng MY, Prayogo D (2014) Symbiotic organisms search: a new metaheuristic optimization algorithm. Comput Struct 139:98\u2013112. https:\/\/doi.org\/10.1016\/j.compstruc.2014.03.007","journal-title":"Comput Struct"},{"key":"852_CR186","doi-asserted-by":"publisher","DOI":"10.1016\/j.mechmachtheory.2006.02.004","author":"BR Rao","year":"2007","unstructured":"Rao BR, Tiwari R (2007) Optimum design of rolling element bearings using genetic algorithms. Mech Mach Theory. https:\/\/doi.org\/10.1016\/j.mechmachtheory.2006.02.004","journal-title":"Mech Mach Theory"},{"key":"852_CR187","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\u2014a 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"},{"issue":"5\u20136","key":"852_CR188","doi-asserted-by":"publisher","first-page":"3951","DOI":"10.1016\/j.apm.2015.10.040","volume":"40","author":"P Savsani","year":"2016","unstructured":"Savsani P, Savsani V (2016) Passing vehicle search (PVS): a novel metaheuristic algorithm. Appl Math Model 40(5\u20136):3951\u20133978. https:\/\/doi.org\/10.1016\/j.apm.2015.10.040","journal-title":"Appl Math Model"},{"issue":"1\u20133","key":"852_CR189","doi-asserted-by":"publisher","first-page":"337","DOI":"10.1080\/03052159908941377","volume":"31","author":"CAC Coello","year":"1999","unstructured":"Coello CAC, 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":"852_CR190","doi-asserted-by":"publisher","first-page":"45","DOI":"10.1016\/j.apm.2019.02.004","volume":"71","author":"H Chen","year":"2019","unstructured":"Chen H, Xu Y, Wang M, Zhao X (2019) A balanced whale optimization algorithm for constrained engineering design problems. Appl Math Model 71:45\u201359. https:\/\/doi.org\/10.1016\/j.apm.2019.02.004","journal-title":"Appl Math Model"},{"issue":"2","key":"852_CR191","doi-asserted-by":"publisher","first-page":"210","DOI":"10.1115\/1.1561044","volume":"125","author":"GG Wang","year":"2003","unstructured":"Wang GG (2003) Adaptive response surface method using inherited Latin hypercube design points. J Mech Des Trans ASME 125(2):210\u2013220. https:\/\/doi.org\/10.1115\/1.1561044","journal-title":"J Mech Des Trans ASME"},{"key":"852_CR192","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2020.113548","author":"M Wang","year":"2020","unstructured":"Wang M, Heidari AA, Chen M, Chen H, Zhao X, Cai X (2020) Exploratory differential ant lion-based optimization. Expert Syst Appl. https:\/\/doi.org\/10.1016\/j.eswa.2020.113548","journal-title":"Expert Syst Appl"},{"key":"852_CR193","doi-asserted-by":"publisher","first-page":"65","DOI":"10.1016\/j.advengsoft.2015.11.004","volume":"92","author":"MD Li","year":"2016","unstructured":"Li MD, Zhao H, Weng XW, Han T (2016) A novel nature-inspired algorithm for optimization: virus colony search. Adv Eng Softw 92:65\u201388. https:\/\/doi.org\/10.1016\/j.advengsoft.2015.11.004","journal-title":"Adv Eng Softw"},{"key":"852_CR194","doi-asserted-by":"publisher","DOI":"10.1007\/s00170-016-9523-2","author":"H Abderazek","year":"2016","unstructured":"Abderazek H, Ferhat D, Ivana A (2016) Adaptive mixed differential evolution algorithm for bi-objective tooth profile spur gear optimization. Int J Adv Manuf Technol. https:\/\/doi.org\/10.1007\/s00170-016-9523-2","journal-title":"Int J Adv Manuf Technol"},{"key":"852_CR195","doi-asserted-by":"publisher","first-page":"3665","DOI":"10.1007\/s00366-020-01025-8","volume":"37","author":"Z Wang","year":"2020","unstructured":"Wang Z, Luo Q, Zhou Y (2020) Hybrid metaheuristic algorithm using butterfly and flower pollination base on mutualism mechanism for global optimization problems. Eng Comput 37:3665\u20133698. https:\/\/doi.org\/10.1007\/s00366-020-01025-8","journal-title":"Eng Comput"}],"container-title":["Complex &amp; Intelligent Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s40747-022-00852-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s40747-022-00852-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s40747-022-00852-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,4,18]],"date-time":"2023-04-18T09:29:48Z","timestamp":1681810188000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s40747-022-00852-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,9,21]]},"references-count":195,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2023,4]]}},"alternative-id":["852"],"URL":"https:\/\/doi.org\/10.1007\/s40747-022-00852-0","relation":{},"ISSN":["2199-4536","2198-6053"],"issn-type":[{"value":"2199-4536","type":"print"},{"value":"2198-6053","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,9,21]]},"assertion":[{"value":"23 March 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 August 2022","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 September 2022","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 contributed to (a) the study\u2019s idea and design, as well as the data analysis and interpretation; (b) the article\u2019s writing or critical revision for key intellectual content; and (c) the final version\u2019s approval. This work has not been submitted to, and is not currently being reviewed by, any other journal or publication venue. The writers are not affiliated with any entity that has a direct or indirect financial interest in the manuscript\u2019s subject matter. There are no writers who have declared a conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}