{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T15:25:38Z","timestamp":1774452338937,"version":"3.50.1"},"reference-count":43,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2023,8,22]],"date-time":"2023-08-22T00:00:00Z","timestamp":1692662400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,8,22]],"date-time":"2023-08-22T00:00:00Z","timestamp":1692662400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100017623","name":"Zhejiang Provincial Outstanding Youth Science Foundation","doi-asserted-by":"publisher","award":["LQ20F020014"],"award-info":[{"award-number":["LQ20F020014"]}],"id":[{"id":"10.13039\/501100017623","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004731","name":"Natural Science Foundation of Zhejiang Province","doi-asserted-by":"publisher","award":["LZJMD23D050001"],"award-info":[{"award-number":["LZJMD23D050001"]}],"id":[{"id":"10.13039\/501100004731","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Memetic Comp."],"published-print":{"date-parts":[[2023,9]]},"DOI":"10.1007\/s12293-023-00394-z","type":"journal-article","created":{"date-parts":[[2023,8,22]],"date-time":"2023-08-22T06:01:50Z","timestamp":1692684110000},"page":"301-317","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Dynamic matrix-based evolutionary algorithm for large-scale sparse multiobjective optimization problems"],"prefix":"10.1007","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0218-765X","authenticated-orcid":false,"given":"Feiyue","family":"Qiu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Huizhen","family":"Hu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jin","family":"Ren","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Liping","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaotian","family":"Pan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qicang","family":"Qiu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,8,22]]},"reference":[{"key":"394_CR1","doi-asserted-by":"crossref","unstructured":"Li H, Shui Y, Sun J, Zhang Q (2021) Approximating pareto fronts in evolutionary multiobjective optimization with large population size. In: International conference on evolutionary multi-criterion optimization. Springer, pp 65\u201376","DOI":"10.1007\/978-3-030-72062-9_6"},{"issue":"4","key":"394_CR2","doi-asserted-by":"publisher","first-page":"2719","DOI":"10.1007\/s40747-021-00352-7","volume":"8","author":"HL Zhen","year":"2022","unstructured":"Zhen HL, Wang Z, Li X, Zhang Q, Yuan M, Zeng J (2022) Accelerate the optimization of large-scale manufacturing planning using game theory. Complex Intell Syst 8(4):2719\u20132730","journal-title":"Complex Intell Syst"},{"issue":"6","key":"394_CR3","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"},{"issue":"8","key":"394_CR4","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 54(8):1\u201334","journal-title":"ACM Comput Surv"},{"issue":"4","key":"394_CR5","doi-asserted-by":"publisher","first-page":"423","DOI":"10.1007\/s12293-022-00377-6","volume":"14","author":"L Chen","year":"2022","unstructured":"Chen L, Liu H, Liu HL, Gu F (2022) A bi-level transformation based evolutionary algorithm framework for equality constrained optimization. Memetic Comput 14(4):423\u2013432","journal-title":"Memetic Comput"},{"key":"394_CR6","doi-asserted-by":"crossref","unstructured":"Ku J, Zhen H, Gong W (2022) Offline data-driven optimization based on dual-scale surrogate ensemble. Memetic Comput 1\u201316","DOI":"10.1007\/s12293-022-00380-x"},{"issue":"3","key":"394_CR7","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"},{"key":"394_CR8","unstructured":"Liang J, Gong M, Li H, Yue C, Qu B (2018) Problem definitions and evaluation criteria for the CEC special session on evolutionary algorithms for sparse optimization. Technical Report, Computational Intelligence Laboratory, Zhengzhou University, Zhengzhou, China, Report# 2018001"},{"key":"394_CR9","unstructured":"Jin Y, Okabe T, Sendhoff B (2004) Neural network regularization and ensembling using multi-objective evolutionary algorithms. In: Proceedings of the 2004 congress on evolutionary computation. IEEE, pp 1\u20138"},{"issue":"4","key":"394_CR10","doi-asserted-by":"publisher","first-page":"497","DOI":"10.1007\/s12293-021-00349-2","volume":"13","author":"J Yuan","year":"2021","unstructured":"Yuan J (2021) Dynamic grid-based uniform search for solving constrained multiobjective optimization problems. Memetic Comput 13(4):497\u2013508","journal-title":"Memetic Comput"},{"issue":"2","key":"394_CR11","doi-asserted-by":"publisher","first-page":"165","DOI":"10.1007\/s12293-022-00358-9","volume":"14","author":"H Hong","year":"2022","unstructured":"Hong H, Ye K, Jiang M, Cao D, Tan KC (2022) Solving large-scale multiobjective optimization via the probabilistic prediction model. Memetic Comput 14(2):165\u2013177","journal-title":"Memetic Comput"},{"issue":"3","key":"394_CR12","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":"394_CR13","doi-asserted-by":"publisher","first-page":"256","DOI":"10.1016\/j.future.2017.10.015","volume":"82","author":"B Cao","year":"2018","unstructured":"Cao B, Zhao J, Yang P, Lv Z, Liu X, Kang X, Yang S, Kang K, Anvari-Moghaddam A (2018) Distributed parallel cooperative coevolutionary multi-objective large-scale immune algorithm for deployment of wireless sensor networks. Futur Gener Comput Syst 82:256\u2013267","journal-title":"Futur Gener Comput Syst"},{"issue":"1","key":"394_CR14","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":"394_CR15","doi-asserted-by":"crossref","unstructured":"Qian H, Yu Y (2017) Solving high-dimensional multi-objective optimization problems with low effective dimensions. In: Proceedings of the AAAI conference on artificial intelligence, pp 1\u20137","DOI":"10.1609\/aaai.v31i1.10664"},{"key":"394_CR16","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2020.106120","volume":"89","author":"R Liu","year":"2020","unstructured":"Liu R, Ren R, Liu J, Liu J (2020) A clustering and dimensionality reduction based evolutionary algorithm for large-scale multi-objective problems. Appl Soft Comput 89:106120","journal-title":"Appl Soft Comput"},{"issue":"6","key":"394_CR17","doi-asserted-by":"publisher","first-page":"3115","DOI":"10.1109\/TCYB.2020.2979930","volume":"51","author":"Y Tian","year":"2020","unstructured":"Tian Y, Lu C, Zhang X, Tan KC, Jin Y (2020) Solving large-scale multiobjective optimization problems with sparse optimal solutions via unsupervised neural networks. IEEE Trans Cybern 51(6):3115\u20133128","journal-title":"IEEE Trans Cybern"},{"key":"394_CR18","doi-asserted-by":"crossref","unstructured":"Zille H, Ishibuchi H, Mostaghim S, Nojima Y (2016) Mutation operators based on variable grouping for multi-objective large-scale optimization. In: 2016 IEEE symposium series on computational intelligence. IEEE, pp 1\u20138","DOI":"10.1109\/SSCI.2016.7850214"},{"key":"394_CR19","doi-asserted-by":"publisher","first-page":"470","DOI":"10.1016\/j.ins.2018.10.005","volume":"509","author":"JH Yi","year":"2020","unstructured":"Yi JH, Xing LN, Wang GG, Dong J, Vasilakos AV, Alavi AH, Wang L (2020) Behavior of crossover operators in NSGA-III for large-scale optimization problems. Inf Sci 509:470\u2013487","journal-title":"Inf Sci"},{"key":"394_CR20","doi-asserted-by":"publisher","first-page":"1078","DOI":"10.1016\/j.asoc.2014.08.024","volume":"24","author":"S Hosseini","year":"2014","unstructured":"Hosseini S, Al Khaled A (2014) A survey on the imperialist competitive algorithm metaheuristic: implementation in engineering domain and directions for future research. Appl Soft Comput 24:1078\u20131094","journal-title":"Appl Soft Comput"},{"issue":"8","key":"394_CR21","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":"12","key":"394_CR22","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 et al (2016) Test problems for large-scale multiobjective and many-objective optimization. IEEE Trans Cybern 47(12):4108\u20134121","journal-title":"IEEE Trans Cybern"},{"key":"394_CR23","doi-asserted-by":"crossref","unstructured":"Vincent P, Larochelle H, Bengio Y, Manzagol PA (2008) Extracting and composing robust features with denoising autoencoders. In: Proceedings of the 25th international conference on machine learning, pp 1096\u20131103","DOI":"10.1145\/1390156.1390294"},{"issue":"1","key":"394_CR24","doi-asserted-by":"publisher","first-page":"69","DOI":"10.1162\/EVCO_a_00122","volume":"23","author":"H Wang","year":"2015","unstructured":"Wang H, Jiao L, Shang R, He S, Liu F (2015) A memetic optimization strategy based on dimension reduction in decision space. Evol Comput 23(1):69\u2013100","journal-title":"Evol Comput"},{"key":"394_CR25","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. IEEE, pp 1\u20138","DOI":"10.1109\/SSCI.2017.8280887"},{"issue":"2","key":"394_CR26","doi-asserted-by":"publisher","first-page":"380","DOI":"10.1109\/TEVC.2019.2918140","volume":"24","author":"Y Tian","year":"2019","unstructured":"Tian Y, Zhang X, Wang C, Jin Y (2019) An evolutionary algorithm for large-scale sparse multiobjective optimization problems. IEEE Trans Evol Comput 24(2):380\u2013393","journal-title":"IEEE Trans Evol Comput"},{"issue":"5","key":"394_CR27","doi-asserted-by":"publisher","first-page":"859","DOI":"10.1109\/TEVC.2021.3111209","volume":"26","author":"X Wang","year":"2021","unstructured":"Wang X, Zhang K, Wang J, Jin Y (2021) An enhanced competitive swarm optimizer with strongly convex sparse operator for large-scale multi-objective optimization. IEEE Trans Evol Comput 26(5):859\u2013871","journal-title":"IEEE Trans Evol Comput"},{"issue":"7","key":"394_CR28","doi-asserted-by":"publisher","first-page":"6784","DOI":"10.1109\/TCYB.2020.3041325","volume":"52","author":"Y Tian","year":"2020","unstructured":"Tian Y, Lu C, Zhang X, Cheng F, Jin Y (2020) A pattern mining-based evolutionary algorithm for large-scale sparse multiobjective optimization problems. IEEE Trans Cybern 52(7):6784\u20136797","journal-title":"IEEE Trans Cybern"},{"issue":"6","key":"394_CR29","doi-asserted-by":"publisher","first-page":"3115","DOI":"10.1109\/TCYB.2020.2979930","volume":"51","author":"Y Tian","year":"2020","unstructured":"Tian Y, Lu C, Zhang X, Tan KC, Jin Y (2020) Solving large-scale multiobjective optimization problems with sparse optimal solutions via unsupervised neural networks. IEEE Trans Cybern 51(6):3115\u20133128","journal-title":"IEEE Trans Cybern"},{"issue":"9","key":"394_CR30","doi-asserted-by":"publisher","first-page":"9695","DOI":"10.1109\/TCYB.2021.3053944","volume":"52","author":"F Cheng","year":"2021","unstructured":"Cheng F, Chu F, Xu Y, Zhang L (2021) A steering-matrix-based multiobjective evolutionary algorithm for high-dimensional feature selection. IEEE Trans Cybern 52(9):9695\u20139708","journal-title":"IEEE Trans Cybern"},{"key":"394_CR31","doi-asserted-by":"crossref","unstructured":"Antonio LM, Coello CAC (2013) Use of cooperative coevolution for solving large scale multiobjective optimization problems. In: 2013 IEEE congress on evolutionary computation. IEEE, pp 2758\u20132765","DOI":"10.1109\/CEC.2013.6557903"},{"key":"394_CR32","first-page":"30","volume":"26","author":"K Deb","year":"1996","unstructured":"Deb K, Goyal M et al (1996) A combined genetic adaptive search (GeneAS) for engineering design. Comput Sci Inf 26:30\u201345","journal-title":"Comput Sci Inf"},{"issue":"6","key":"394_CR33","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"},{"issue":"2","key":"394_CR34","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, Yin M, 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":"4","key":"394_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"},{"key":"394_CR36","doi-asserted-by":"crossref","unstructured":"Ishibuchi H, Sakane Y, Tsukamoto N, Nojima Y (2009) Evolutionary many-objective optimization by NSGA-II and MOEA\/D with large populations. In: 2009 IEEE international conference on systems, man and cybernetics. IEEE, pp 1758\u20131763","DOI":"10.1109\/ICSMC.2009.5346628"},{"issue":"2","key":"394_CR37","first-page":"115","volume":"9","author":"K Deb","year":"1995","unstructured":"Deb K, Agrawal RB et al (1995) Simulated binary crossover for continuous search space. Complex Syst 9(2):115\u2013148","journal-title":"Complex Syst"},{"key":"394_CR38","doi-asserted-by":"crossref","unstructured":"Batagelj V, Mrvar A (2014) Pajek. pp 1245\u20131256","DOI":"10.1007\/978-1-4614-6170-8_310"},{"issue":"1","key":"394_CR39","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1016\/j.swevo.2011.02.002","volume":"1","author":"J Derrac","year":"2011","unstructured":"Derrac J, Garc\u00eda S, Molina D, Herrera F (2011) A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithms. Swarm Evol Comput 1(1):3\u201318","journal-title":"Swarm Evol Comput"},{"key":"394_CR40","doi-asserted-by":"publisher","first-page":"208","DOI":"10.1016\/j.ins.2020.11.011","volume":"553","author":"Y Zhang","year":"2021","unstructured":"Zhang Y, Mei Y, Zhang B, Jiang K (2021) Divide-and-conquer large scale capacitated arc routing problems with route cutting off decomposition. Inf Sci 553:208\u2013224","journal-title":"Inf Sci"},{"key":"394_CR41","doi-asserted-by":"publisher","first-page":"118571","DOI":"10.1109\/ACCESS.2021.3107163","volume":"9","author":"N Shvetsova","year":"2021","unstructured":"Shvetsova N, Bakker B, Fedulova I, Schulz H, Dylov DV (2021) Anomaly detection in medical imaging with deep perceptual autoencoders. IEEE Access 9:118571\u2013118583","journal-title":"IEEE Access"},{"key":"394_CR42","doi-asserted-by":"crossref","unstructured":"Wang S, Jiang Z, Bao X (2021) Autonomous trajectory planning method for multi-UAV collaborative search. In: 2021 5th international conference on automation, control and robots. IEEE, pp 84\u201388","DOI":"10.1109\/ICACR53472.2021.9605170"},{"issue":"2","key":"394_CR43","doi-asserted-by":"publisher","first-page":"264","DOI":"10.1109\/TEVC.2014.2315442","volume":"19","author":"H Ishibuchi","year":"2014","unstructured":"Ishibuchi H, Akedo N, Nojima Y (2014) Behavior of multiobjective evolutionary algorithms on many-objective knapsack problems. IEEE Trans Evol Comput 19(2):264\u2013283","journal-title":"IEEE Trans Evol Comput"}],"container-title":["Memetic Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12293-023-00394-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s12293-023-00394-z\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12293-023-00394-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,7]],"date-time":"2023-09-07T08:39:20Z","timestamp":1694075960000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s12293-023-00394-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,8,22]]},"references-count":43,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2023,9]]}},"alternative-id":["394"],"URL":"https:\/\/doi.org\/10.1007\/s12293-023-00394-z","relation":{},"ISSN":["1865-9284","1865-9292"],"issn-type":[{"value":"1865-9284","type":"print"},{"value":"1865-9292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,8,22]]},"assertion":[{"value":"21 June 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 July 2023","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"22 August 2023","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}