{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,13]],"date-time":"2026-06-13T16:41:37Z","timestamp":1781368897381,"version":"3.54.1"},"reference-count":59,"publisher":"Springer Science and Business Media LLC","issue":"5","license":[{"start":{"date-parts":[[2022,12,27]],"date-time":"2022-12-27T00:00:00Z","timestamp":1672099200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2022,12,27]],"date-time":"2022-12-27T00:00:00Z","timestamp":1672099200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100010909","name":"Young Scientists Fund","doi-asserted-by":"publisher","award":["61906010"],"award-info":[{"award-number":["61906010"]}],"id":[{"id":"10.13039\/501100010909","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100010905","name":"Major Research Plan","doi-asserted-by":"publisher","award":["61672065"],"award-info":[{"award-number":["61672065"]}],"id":[{"id":"10.13039\/501100010905","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003213","name":"Beijing Municipal Education Commission","doi-asserted-by":"publisher","award":["KM202010005032"],"award-info":[{"award-number":["KM202010005032"]}],"id":[{"id":"10.13039\/501100003213","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput &amp; Applic"],"published-print":{"date-parts":[[2023,2]]},"DOI":"10.1007\/s00521-022-08133-0","type":"journal-article","created":{"date-parts":[[2022,12,27]],"date-time":"2022-12-27T16:02:41Z","timestamp":1672156961000},"page":"3767-3788","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["A dual decomposition strategy for large-scale multiobjective evolutionary optimization"],"prefix":"10.1007","volume":"35","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4471-7447","authenticated-orcid":false,"given":"Cuicui","family":"Yang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Peike","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junzhong","family":"Ji","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2022,12,27]]},"reference":[{"issue":"3","key":"8133_CR1","doi-asserted-by":"publisher","first-page":"321","DOI":"10.1109\/TEVC.2012.2196800","volume":"17","author":"A Ponsich","year":"2012","unstructured":"Ponsich A, Jaimes AL, Coello CAC (2012) A survey on multiobjective evolutionary algorithms for the solution of the portfolio optimization problem and other finance and economics applications. IEEE Trans Evol Comput 17(3):321\u2013344","journal-title":"IEEE Trans Evol Comput"},{"issue":"1","key":"8133_CR2","doi-asserted-by":"publisher","first-page":"1502242","DOI":"10.1080\/23311916.2018.1502242","volume":"5","author":"N Gunantara","year":"2018","unstructured":"Gunantara N (2018) A review of multi-objective optimization: methods and its applications. Cogent Eng 5(1):1502242","journal-title":"Cogent Eng"},{"issue":"2","key":"8133_CR3","doi-asserted-by":"publisher","first-page":"69","DOI":"10.1504\/IJBIC.2019.101640","volume":"14","author":"M Ojha","year":"2019","unstructured":"Ojha M, Singh KP, Chakraborty P, Verma S (2019) A review of multi-objective optimisation and decision making using evolutionary algorithms. Int J Bio Inspir Comput 14(2):69\u201384","journal-title":"Int J Bio Inspir Comput"},{"issue":"2","key":"8133_CR4","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3376916","volume":"53","author":"JG Falc\u00f3n-Cardona","year":"2020","unstructured":"Falc\u00f3n-Cardona JG, Coello CAC (2020) Indicator-based multi-objective evolutionary algorithms: a comprehensive survey. ACM Comput Surv (CSUR) 53(2):1\u201335","journal-title":"ACM Comput Surv (CSUR)"},{"key":"8133_CR5","doi-asserted-by":"crossref","unstructured":"Drechsler N, Drechsler R, Becker B (1999) Multi-objective optimization in evolutionary algorithms using satisfiability classes. In: International conference on computational intelligence, pp 108\u2013117","DOI":"10.1007\/3-540-48774-3_14"},{"issue":"4","key":"8133_CR6","doi-asserted-by":"publisher","first-page":"634","DOI":"10.1109\/TEVC.2020.2978158","volume":"24","author":"X Ma","year":"2020","unstructured":"Ma X, Yu Y, Li X, Qi Y, Zhu Z (2020) A survey of weight vector adjustment methods for decomposition-based multiobjective evolutionary algorithms. IEEE Trans Evol Comput 24(4):634\u2013649","journal-title":"IEEE Trans Evol Comput"},{"issue":"8","key":"8133_CR7","first-page":"1","volume":"54","author":"Y Tian","year":"2021","unstructured":"Tian Y, Si L, Zhang X, Cheng R, He C, Tan KC, Jin Y (2021) Evolutionary large-scale multi-objective optimization: a survey. ACM Comput Surv (CSUR) 54(8):1\u201334","journal-title":"ACM Comput Surv (CSUR)"},{"issue":"2","key":"8133_CR8","doi-asserted-by":"publisher","first-page":"275","DOI":"10.1109\/TEVC.2015.2455812","volume":"20","author":"X Ma","year":"2015","unstructured":"Ma X, Liu F, Qi Y, Wang X, Li L, Jiao L, Gong M (2015) A multiobjective evolutionary algorithm based on decision variable analyses for multiobjective optimization problems with large-scale variables. IEEE Trans Evol Comput 20(2):275\u2013298","journal-title":"IEEE Trans Evol Comput"},{"issue":"1","key":"8133_CR9","doi-asserted-by":"publisher","first-page":"97","DOI":"10.1109\/TEVC.2016.2600642","volume":"22","author":"X Zhang","year":"2016","unstructured":"Zhang X, Tian Y, Cheng R, Jin Y (2016) A decision variable clustering-based evolutionary algorithm for large-scale many-objective optimization. IEEE Trans Evol Comput 22(1):97\u2013112","journal-title":"IEEE Trans Evol Comput"},{"key":"8133_CR10","doi-asserted-by":"publisher","DOI":"10.1109\/TEVC.2021.3130835","author":"M Omidvar","year":"2021","unstructured":"Omidvar M, Li X, Yao X (2021) A review of population-based metaheuristics for large-scale black-box global optimization: part B. IEEE Trans Evol Comput. https:\/\/doi.org\/10.1109\/TEVC.2021.3130835","journal-title":"IEEE Trans Evol Comput"},{"key":"8133_CR11","doi-asserted-by":"crossref","unstructured":"Oldewage ET, Engelbrecht AP, Cleghorn CW (2017) The merits of velocity clamping particle swarm optimisation in high dimensional spaces. In: 2017 IEEE symposium series on computational intelligence, pp 1\u20138","DOI":"10.1109\/SSCI.2017.8280887"},{"issue":"2","key":"8133_CR12","doi-asserted-by":"publisher","first-page":"460","DOI":"10.1016\/j.ejor.2017.02.015","volume":"261","author":"K Deb","year":"2017","unstructured":"Deb K, Myburgh C (2017) A population-based fast algorithm for a billion-dimensional resource allocation problem with integer variables. Eur J Oper Res 261(2):460\u2013474","journal-title":"Eur J Oper Res"},{"key":"8133_CR13","doi-asserted-by":"crossref","unstructured":"Song A, Yang Q, Chen W-N, Zhang J (2016) A random-based dynamic grouping strategy for large scale multi-objective optimization. In: 2016 IEEE congress on evolutionary computation, pp 468\u2013475","DOI":"10.1109\/CEC.2016.7743831"},{"issue":"3","key":"8133_CR14","doi-asserted-by":"publisher","first-page":"378","DOI":"10.1109\/TEVC.2013.2281543","volume":"18","author":"MN Omidvar","year":"2013","unstructured":"Omidvar MN, Li X, Mei Y, Yao X (2013) Cooperative co-evolution with differential grouping for large scale optimization. IEEE Trans Evol Comput 18(3):378\u2013393","journal-title":"IEEE Trans Evol Comput"},{"issue":"2","key":"8133_CR15","doi-asserted-by":"publisher","first-page":"260","DOI":"10.1109\/TEVC.2017.2704782","volume":"22","author":"H Zille","year":"2017","unstructured":"Zille H, Ishibuchi H, Mostaghim S, Nojima Y (2017) A framework for large-scale multiobjective optimization based on problem transformation. IEEE Trans Evol Comput 22(2):260\u2013275","journal-title":"IEEE Trans Evol Comput"},{"issue":"3","key":"8133_CR16","doi-asserted-by":"publisher","first-page":"435","DOI":"10.1109\/TEVC.2013.2281503","volume":"18","author":"Y Mei","year":"2013","unstructured":"Mei Y, Li X, Yao X (2013) Cooperative coevolution with route distance grouping for large-scale capacitated arc routing problems. IEEE Trans Evol Comput 18(3):435\u2013449","journal-title":"IEEE Trans Evol Comput"},{"issue":"15","key":"8133_CR17","doi-asserted-by":"publisher","first-page":"2985","DOI":"10.1016\/j.ins.2008.02.017","volume":"178","author":"Z Yang","year":"2008","unstructured":"Yang Z, Tang K, Yao X (2008) Large scale evolutionary optimization using cooperative coevolution. Inf Sci 178(15):2985\u20132999","journal-title":"Inf Sci"},{"issue":"3","key":"8133_CR18","doi-asserted-by":"publisher","first-page":"225","DOI":"10.1109\/TEVC.2004.826069","volume":"8","author":"F Van den Bergh","year":"2004","unstructured":"Van den Bergh F, Engelbrecht AP (2004) A cooperative approach to particle swarm optimization. IEEE Trans Evol Comput 8(3):225\u2013239","journal-title":"IEEE Trans Evol Comput"},{"key":"8133_CR19","doi-asserted-by":"crossref","unstructured":"Chen W, Weise T, Yang Z, Tang K (2010) Large-scale global optimization using cooperative coevolution with variable interaction learning. In: International conference on parallel problem solving from nature, pp 300\u2013309","DOI":"10.1007\/978-3-642-15871-1_31"},{"issue":"3","key":"8133_CR20","doi-asserted-by":"publisher","first-page":"378","DOI":"10.1109\/TEVC.2013.2281543","volume":"18","author":"MN Omidvar","year":"2013","unstructured":"Omidvar MN, Li X, Mei Y, Yao X (2013) Cooperative co-evolution with differential grouping for large scale optimization. IEEE Trans Evol Comput 18(3):378\u2013393","journal-title":"IEEE Trans Evol Comput"},{"key":"8133_CR21","doi-asserted-by":"crossref","unstructured":"Li L, He C, Cheng R, Pan L (2021) Large-scale multiobjective optimization via problem decomposition and reformulation. In: 2021 IEEE congress on evolutionary computation, pp 2149\u20132155","DOI":"10.1109\/CEC45853.2021.9504820"},{"issue":"8","key":"8133_CR22","doi-asserted-by":"publisher","first-page":"3696","DOI":"10.1109\/TCYB.2019.2906383","volume":"50","author":"Y Tian","year":"2019","unstructured":"Tian Y, Zheng X, Zhang X, Jin Y (2019) Efficient large-scale multiobjective optimization based on a competitive swarm optimizer. IEEE Trans Cybern 50(8):3696\u20133708","journal-title":"IEEE Trans Cybern"},{"issue":"2","key":"8133_CR23","doi-asserted-by":"publisher","first-page":"786","DOI":"10.1109\/TSMC.2020.3003926","volume":"52","author":"C He","year":"2020","unstructured":"He C, Cheng R, Yazdani D (2020) Adaptive offspring generation for evolutionary large-scale multiobjective optimization. IEEE Trans Syst Man Cybern 52(2):786\u2013798","journal-title":"IEEE Trans Syst Man Cybern"},{"issue":"4","key":"8133_CR24","doi-asserted-by":"publisher","first-page":"724","DOI":"10.1109\/TEVC.2021.3063606","volume":"25","author":"S Qin","year":"2021","unstructured":"Qin S, Sun C, Jin Y, Tan Y, Fieldsend J (2021) Large-scale evolutionary multiobjective optimization assisted by directed sampling. IEEE Trans Evol Comput 25(4):724\u2013738","journal-title":"IEEE Trans Evol Comput"},{"key":"8133_CR25","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2021.3113158","author":"Z Wang","year":"2021","unstructured":"Wang Z, Hong H, Ye K, Zhang G-E, Jiang M, Tan KC (2021) Manifold interpolation for large-scale multiobjective optimization via generative adversarial networks. IEEE Trans Neural Netw Learn Syst. https:\/\/doi.org\/10.1109\/TNNLS.2021.3113158","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"issue":"1","key":"8133_CR26","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1007\/s10107-015-0892-3","volume":"151","author":"SJ Wright","year":"2015","unstructured":"Wright SJ (2015) Coordinate descent algorithms. Math Program 151(1):3\u201334","journal-title":"Math Program"},{"key":"8133_CR27","first-page":"1","volume":"60","author":"P Huang","year":"2022","unstructured":"Huang P, Zou Z, Xia XG, Liu X, Liao G (2022) A novel dimension-reduced space-time adaptive processing algorithm for spaceborne multichannel surveillance radar systems based on spatial-temporal 2-D sliding window. IEEE Trans Geosci Remote Sens 60:1\u201321","journal-title":"IEEE Trans Geosci Remote Sens"},{"issue":"4","key":"8133_CR28","doi-asserted-by":"publisher","first-page":"3338","DOI":"10.1109\/JIOT.2020.2967119","volume":"7","author":"P Koshy","year":"2020","unstructured":"Koshy P, Babu S, Manoj BS (2020) Sliding window blockchain architecture for internet of things. IEEE Internet Things J 7(4):3338\u20133348","journal-title":"IEEE Internet Things J"},{"key":"8133_CR29","doi-asserted-by":"crossref","unstructured":"Jiang D, Liu J, Xu Z, Qin W (2011) Network traffic anomaly detection based on sliding window. In: 2011 International conference on electrical and control engineering, pp 4830\u20134833","DOI":"10.1109\/ICECENG.2011.6057677"},{"key":"8133_CR30","doi-asserted-by":"crossref","unstructured":"Coello Coello CA, Reyes Sierra M (2004) A study of the parallelization of a coevolutionary multi-objective evolutionary algorithm. In: Mexican international conference on artificial intelligence, pp 688\u2013697","DOI":"10.1007\/978-3-540-24694-7_71"},{"issue":"12","key":"8133_CR31","doi-asserted-by":"publisher","first-page":"4108","DOI":"10.1109\/TCYB.2016.2600577","volume":"47","author":"R Cheng","year":"2016","unstructured":"Cheng R, Jin Y, Olhofer M (2016) Test problems for large-scale multiobjective and many-objective optimization. IEEE Trans Cybern 47(12):4108\u20134121","journal-title":"IEEE Trans Cybern"},{"issue":"6","key":"8133_CR32","doi-asserted-by":"publisher","first-page":"712","DOI":"10.1109\/TEVC.2007.892759","volume":"11","author":"Q Zhang","year":"2007","unstructured":"Zhang Q, Li H (2007) MOEA\/D: a multiobjective evolutionary algorithm based on decomposition. IEEE Trans Evol Comput 11(6):712\u2013731","journal-title":"IEEE Trans Evol Comput"},{"key":"8133_CR33","volume-title":"Differential evolution: a practical approach to global optimization","author":"K Price","year":"2006","unstructured":"Price K, Storn RM, Lampinen JA (2006) Differential evolution: a practical approach to global optimization. Springer Science Business Media, Berlin"},{"issue":"2","key":"8133_CR34","doi-asserted-by":"publisher","first-page":"284","DOI":"10.1109\/TEVC.2008.925798","volume":"13","author":"H Li","year":"2008","unstructured":"Li H, Zhang Q (2008) Multiobjective optimization problems with complicated Pareto sets, MOEA\/D and NSGA-II. IEEE Trans Evol Comput 13(2):284\u2013302","journal-title":"IEEE Trans Evol Comput"},{"issue":"4","key":"8133_CR35","doi-asserted-by":"publisher","first-page":"73","DOI":"10.1109\/MCI.2017.2742868","volume":"12","author":"Y Tian","year":"2017","unstructured":"Tian Y, Cheng R, Zhang X, Jin Y (2017) PlatEMO: a MATLAB platform for evolutionary multi-objective optimization [educational forum]. IEEE Comput Intell Mag 12(4):73\u201387","journal-title":"IEEE Comput Intell Mag"},{"issue":"5","key":"8133_CR36","doi-asserted-by":"publisher","first-page":"792","DOI":"10.1109\/TEVC.2016.2521868","volume":"20","author":"H Zhang","year":"2016","unstructured":"Zhang H, Zhou A, Song S, Zhang Q, Gao X-Z, Zhang J (2016) A self-organizing multiobjective evolutionary algorithm. IEEE Trans Evol Comput 20(5):792\u2013806","journal-title":"IEEE Trans Evol Comput"},{"issue":"5","key":"8133_CR37","doi-asserted-by":"publisher","first-page":"870","DOI":"10.1109\/TEVC.2019.2894743","volume":"23","author":"Z-Z Liu","year":"2019","unstructured":"Liu Z-Z, Wang Y (2019) Handling constrained multiobjective optimization problems with constraints in both the decision and objective spaces. IEEE Trans Evol Comput 23(5):870\u2013884","journal-title":"IEEE Trans Evol Comput"},{"key":"8133_CR38","doi-asserted-by":"crossref","unstructured":"Zhang J, Zhou A, Zhang G (2015) A classification and Pareto domination based multiobjective evolutionary algorithm. In: 2015 IEEE congress on evolutionary computation, pp 2883\u20132890","DOI":"10.1109\/CEC.2015.7257247"},{"issue":"1","key":"8133_CR39","doi-asserted-by":"publisher","first-page":"52","DOI":"10.1109\/TCYB.2015.2507366","volume":"47","author":"H Li","year":"2016","unstructured":"Li H, Zhang Q, Deng JI (2016) Biased multiobjective optimization and decomposition algorithm. IEEE Trans Cybern 47(1):52\u201366","journal-title":"IEEE Trans Cybern"},{"issue":"11","key":"8133_CR40","first-page":"2639","volume":"44","author":"X-Y Zhang","year":"2016","unstructured":"Zhang X-Y, Jiang X-S, Zhang L (2016) A weight vector based multi-objective optimization algorithm with preference. Acta Geosci Sin 44(11):2639","journal-title":"Acta Geosci Sin"},{"issue":"6","key":"8133_CR41","doi-asserted-by":"publisher","first-page":"949","DOI":"10.1109\/TEVC.2019.2896002","volume":"23","author":"C He","year":"2019","unstructured":"He C, Li L, Tian Y, Zhang X, Cheng R, Jin Y, Yao X (2019) Accelerating large-scale multiobjective optimization via problem reformulation. IEEE Trans Evol Comput 23(6):949\u2013961","journal-title":"IEEE Trans Evol Comput"},{"key":"8133_CR42","doi-asserted-by":"publisher","DOI":"10.1109\/TEVC.2021.3118593","author":"X Yang","year":"2021","unstructured":"Yang X, Zou J, Yang S, Zheng J, Liu Y (2021) A fuzzy decision variables framework for large-scale multiobjective optimization. IEEE Trans Evol Comput. https:\/\/doi.org\/10.1109\/TEVC.2021.3118593","journal-title":"IEEE Trans Evol Comput"},{"key":"8133_CR43","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2022.3180214","author":"Y Xu","year":"2022","unstructured":"Xu Y, Xu C, Zhang H, Huang L, Liu Y, Nojima Y, Zeng X (2022) A multi-population multi-objective evolutionary algorithm based on the contribution of decision variables to objectives for large-scale multi\/many-objective optimization. IEEE Trans Cybern. https:\/\/doi.org\/10.1109\/TCYB.2022.3180214","journal-title":"IEEE Trans Cybern"},{"issue":"5","key":"8133_CR44","doi-asserted-by":"publisher","first-page":"868","DOI":"10.1109\/TEVC.2020.2967501","volume":"24","author":"C He","year":"2020","unstructured":"He C, Cheng R, Zhang C, Tian Y, Chen Q, Yao X (2020) Evolutionary large-scale multiobjective optimization for ratio error estimation of voltage transformers. IEEE Trans Evol Comput 24(5):868\u2013881","journal-title":"IEEE Trans Evol Comput"},{"key":"8133_CR45","doi-asserted-by":"crossref","unstructured":"Eykholt K, Evtimov I, Fernandes E, Li B, Rahmati A, Xiao C, Prakash A, Kohno T, Song D (2018) Robust physical-world attacks on deep learning visual classification. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 1625\u20131634","DOI":"10.1109\/CVPR.2018.00175"},{"key":"8133_CR46","unstructured":"Krizhevsky A, Hinton G (2009) Learning multiple layers of features from tiny images"},{"key":"8133_CR47","doi-asserted-by":"publisher","DOI":"10.1109\/TAI.2022.316803","author":"Y Tian","year":"2022","unstructured":"Tian Y, Pan J, Yang S, Zhang X, He S, Jin Y (2022) Imperceptible and sparse adversarial attacks via a dual-population based constrained evolutionary algorithm. IEEE Trans Artif Intell. https:\/\/doi.org\/10.1109\/TAI.2022.316803","journal-title":"IEEE Trans Artif Intell"},{"key":"8133_CR48","doi-asserted-by":"crossref","unstructured":"Carlini N, Wagner D (2017) Towards evaluating the robustness of neural networks In: 2017 IEEE symposium on security and privacy, pp 39\u201357","DOI":"10.1109\/SP.2017.49"},{"key":"8133_CR49","doi-asserted-by":"crossref","unstructured":"Kurakin A, Goodfellow IJ, Bengio S (2018) Adversarial examples in the physical world. In: Artificial intelligence safety and security, pp 99\u2013112","DOI":"10.1201\/9781351251389-8"},{"issue":"5","key":"8133_CR50","doi-asserted-by":"publisher","first-page":"828","DOI":"10.1109\/TEVC.2019.2890858","volume":"23","author":"J Su","year":"2019","unstructured":"Su J, Vargas DV, Sakurai K (2019) One pixel attack for fooling deep neural networks. IEEE Trans Evol Comput 23(5):828\u2013841","journal-title":"IEEE Trans Evol Comput"},{"key":"8133_CR51","unstructured":"Wiyatno R, Xu A (2018) Maximal jacobian-based saliency map attack. arXiv preprint arXiv:1808.07945"},{"key":"8133_CR52","doi-asserted-by":"crossref","unstructured":"Fan Y, Wu B, Li T, Zhang Y, Li M, Li Z, Yang Y (2020) Sparse adversarial attack via perturbation factorization. In: European conference on computer vision, pp 35\u201350","DOI":"10.1007\/978-3-030-58542-6_3"},{"key":"8133_CR53","doi-asserted-by":"crossref","unstructured":"Croce F, Hein M (2019) Sparse and imperceivable adversarial attacks. In: Proceedings of the IEEE\/CVF international conference on computer vision, pp 4724\u20134732","DOI":"10.1109\/ICCV.2019.00482"},{"key":"8133_CR54","unstructured":"Ilyas A, Engstrom L, Athalye A, Lin JI (2018) Black-box adversarial attacks with limited queries and information. In: International conference on machine learning, pp 2137\u20132146"},{"key":"8133_CR55","doi-asserted-by":"crossref","unstructured":"Deng Y, Zhang C, Wang X (2019) A multi-objective examples generation approach to fool the deep neural networks in the black-box scenario. In: 2019 IEEE fourth international conference on data science in cyberspace, pp 92\u201399","DOI":"10.1109\/DSC.2019.00022"},{"key":"8133_CR56","doi-asserted-by":"publisher","first-page":"100843","DOI":"10.1016\/j.swevo.2021.100843","volume":"62","author":"G Li","year":"2021","unstructured":"Li G, Wang W, Zhang W, Wang Z, Tu H, You W (2021) Grid search based multi-population particle swarm optimization algorithm for multimodal multi-objective optimization. Swarm Evol Comput 62:100843","journal-title":"Swarm Evol Comput"},{"issue":"1","key":"8133_CR57","first-page":"26","volume":"17","author":"J Wu","year":"2019","unstructured":"Wu J, Chen XY, Zhang H, Xiong LD, Lei H, Deng SH (2019) Hyperparameter optimization for machine learning models based on Bayesian optimization. J Electron Sci Technol 17(1):26\u201340","journal-title":"J Electron Sci Technol"},{"issue":"1","key":"8133_CR58","doi-asserted-by":"publisher","first-page":"218","DOI":"10.1109\/TITS.2018.2803842","volume":"20","author":"P Dai","year":"2018","unstructured":"Dai P, Liu K, Feng L, Zhang H, Lee VCS, Son SH, Wu X (2018) Temporal information services in large-scale vehicular networks through evolutionary multi-objective optimization. IEEE Trans Intell Syst 20(1):218\u2013231","journal-title":"IEEE Trans Intell Syst"},{"issue":"4","key":"8133_CR59","doi-asserted-by":"publisher","first-page":"329","DOI":"10.1177\/014662168701100401","volume":"11","author":"GW Millig","year":"1987","unstructured":"Millig GW, Cooper MC (1987) Methodology review: clustering methods. Appl Psychol Meas 11(4):329\u2013354","journal-title":"Appl Psychol Meas"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-022-08133-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00521-022-08133-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-022-08133-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,27]],"date-time":"2023-01-27T05:25:54Z","timestamp":1674797154000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00521-022-08133-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,12,27]]},"references-count":59,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2023,2]]}},"alternative-id":["8133"],"URL":"https:\/\/doi.org\/10.1007\/s00521-022-08133-0","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,12,27]]},"assertion":[{"value":"21 February 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 November 2022","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"27 December 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":"The authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}