{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,18]],"date-time":"2026-07-18T22:28:37Z","timestamp":1784413717158,"version":"3.55.0"},"reference-count":51,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T00:00:00Z","timestamp":1769904000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T00:00:00Z","timestamp":1769904000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Mach. Intell. Res."],"published-print":{"date-parts":[[2026,2]]},"DOI":"10.1007\/s11633-025-1559-z","type":"journal-article","created":{"date-parts":[[2026,2,2]],"date-time":"2026-02-02T14:11:29Z","timestamp":1770041489000},"page":"263-280","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["A Generative Adversarial Network Guided Evolutionary Algorithm for Large-scale Sparse Multiobjective Optimization"],"prefix":"10.1007","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5910-2795","authenticated-orcid":false,"given":"Zhuanlian","family":"Ding","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junzhe","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0164-7944","authenticated-orcid":false,"given":"Dengdi","family":"Sun","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xingyi","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bin","family":"Luo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,2,2]]},"reference":[{"key":"1559_CR1","doi-asserted-by":"publisher","first-page":"69","DOI":"10.1145\/12130.12138","volume-title":"Proceedings of the 18th Annual ACM Symposium on Theory of Computing","author":"M W Krentel","year":"1986","unstructured":"M. W. Krentel. The complexity of optimization problems. In Proceedings of the 18th Annual ACM Symposium on Theory of Computing, Berkeley, USA, pp. 69\u201376, 1986. DOI: https:\/\/doi.org\/10.1145\/12130.12138."},{"issue":"2","key":"1559_CR2","doi-asserted-by":"publisher","first-page":"145","DOI":"10.1007\/s11633-023-1431-y","volume":"20","author":"J R Wen","year":"2023","unstructured":"J. R. Wen, Z. Huang, H. Zhang. Editorial for special issue on large-scale pre-training: Data, models, and fine-tuning. Machine Intelligence Research, vol. 20, no. 2, pp. 145\u2013146, 2023. DOI: https:\/\/doi.org\/10.1007\/s11633-023-1431-y.","journal-title":"Machine Intelligence Research"},{"key":"1559_CR3","doi-asserted-by":"publisher","first-page":"2758","DOI":"10.1109\/CEC.2013.6557903","volume-title":"Proceedings of Congress on Evolutionary Computation","author":"L M Antonio","year":"2013","unstructured":"L. M. Antonio, C. A. C. Coello. Use of cooperative coevolution for solving large scale multiobjective optimization problems. In Proceedings of Congress on Evolutionary Computation, IEEE, Cancun, Mexico, pp. 2758\u20132765, 2013. DOI: https:\/\/doi.org\/10.1109\/CEC.2013.6557903."},{"issue":"1","key":"1559_CR4","doi-asserted-by":"publisher","first-page":"97","DOI":"10.1109\/TEVC.2016.2600642","volume":"22","author":"X Zhang","year":"2018","unstructured":"X. Zhang, Y. Tian, R. Cheng, Y. Jin. A decision variable clustering-based evolutionary algorithm for large-scale many-objective optimization. IEEE Transactions on Evolutionary Computation, vol. 22, no. 1, pp. 97\u2013112, 2018. DOI: https:\/\/doi.org\/10.1109\/TEVC.2016.2600642.","journal-title":"IEEE Transactions on Evolutionary Computation"},{"issue":"2","key":"1559_CR5","doi-asserted-by":"publisher","first-page":"260","DOI":"10.1109\/TEVC.2017.2704782","volume":"22","author":"H Zille","year":"2018","unstructured":"H. Zille, H. Ishibuchi, S. Mostaghim, Y. Nojima. A framework for large-scale multiobjective optimization based on problem transformation. IEEE Transactions on Evolutionary Computation, vol. 22, no. 2, pp. 260\u2013275, 2018. DOI: https:\/\/doi.org\/10.1109\/TEVC.2017.2704782.","journal-title":"IEEE Transactions on Evolutionary Computation"},{"issue":"6","key":"1559_CR6","doi-asserted-by":"publisher","first-page":"949","DOI":"10.1109\/TEVC.2019.2896002","volume":"23","author":"C He","year":"2019","unstructured":"C. He, L. Li, Y. Tian, X. Zhang, R. Cheng, Y. Jin, X. Yao. Accelerating large-scale multiobjective optimization via problem reformulation. IEEE Transactions on Evolutionary Computation, vol. 23, no. 6, pp. 949\u2013961, 2019. DOI: https:\/\/doi.org\/10.1109\/TEVC.2019.2896002.","journal-title":"IEEE Transactions on Evolutionary Computation"},{"issue":"4","key":"1559_CR7","doi-asserted-by":"publisher","first-page":"724","DOI":"10.1109\/TEVC.2021.3063606","volume":"25","author":"S Qin","year":"2021","unstructured":"S. Qin, C. Sun, Y. Jin, Y. Tan, J. Fieldsend. Large-scale evolutionary multiobjective optimization assisted by directed sampling. IEEE Transactions on Evolutionary Computation, vol. 25, no. 4, pp. 724\u2013738, 2021. DOI: https:\/\/doi.org\/10.1109\/TEVC.2021.3063606.","journal-title":"IEEE Transactions on Evolutionary Computation"},{"issue":"5","key":"1559_CR8","doi-asserted-by":"publisher","first-page":"59","DOI":"10.1109\/MCOM.2006.1637948","volume":"44","author":"P Ojala","year":"2006","unstructured":"P. Ojala, A. Lakaniemi, H. Lepanaho, M. Jokimies. The adaptive multirate wideband speech codec: System characteristics, quality advances, and deployment strategies. IEEE Communications Magazine, vol. 44, no. 5, pp. 59\u201365, 2006. DOI: https:\/\/doi.org\/10.1109\/MCOM.2006.1637948.","journal-title":"IEEE Communications Magazine"},{"issue":"8","key":"1559_CR9","doi-asserted-by":"publisher","first-page":"3696","DOI":"10.1109\/TCYB.2019.2906383","volume":"50","author":"Y Tian","year":"2020","unstructured":"Y. Tian, X. Zheng, X. Zhang, Y. Jin. Efficient large-scale multiobjective optimization based on a competitive swarm optimizer. IEEE Transactions on Cybernetics, vol. 50, no. 8, pp. 3696\u20133708, 2020. DOI: https:\/\/doi.org\/10.1109\/TCYB.2019.2906383.","journal-title":"IEEE Transactions on Cybernetics"},{"key":"1559_CR10","doi-asserted-by":"publisher","first-page":"350","DOI":"10.1109\/CEC.2019.8790351","volume-title":"Proceedings of Congress on Evolutionary Computation","author":"H Hiba","year":"2019","unstructured":"H. Hiba, A. A. Bidgoli, A. Ibrahim, S. Rahnamayan. CGDE3: An efficient center-based algorithm for solving large-scale multi-objective optimization problems. In Proceedings of Congress on Evolutionary Computation, IEEE, Wellington, New Zealand, pp. 350\u2013358, 2019. DOI: https:\/\/doi.org\/10.1109\/CEC.2019.8790351."},{"issue":"3","key":"1559_CR11","doi-asserted-by":"publisher","first-page":"321","DOI":"10.1109\/TEVC.2012.2196800","volume":"17","author":"A Ponsich","year":"2013","unstructured":"A. Ponsich, A. L. Jaimes, C. A. C. Coello. A survey on multiobjective evolutionary algorithms for the solution of the portfolio optimization problem and other finance and economics applications. IEEE Transactions on Evolutionary Computation, vol. 17, no. 3, pp. 321\u2013344, 2013. DOI: https:\/\/doi.org\/10.1109\/TEVC.2012.2196800.","journal-title":"IEEE Transactions on Evolutionary Computation"},{"issue":"2","key":"1559_CR12","doi-asserted-by":"publisher","first-page":"338","DOI":"10.1109\/TNN.2004.841794","volume":"16","author":"J E Fieldsend","year":"2005","unstructured":"J. E. Fieldsend, S. Singh. Pareto evolutionary neural networks. IEEE Transactions on Neural Networks, vol. 16, no. 2, pp. 338\u2013354, 2005. DOI: https:\/\/doi.org\/10.1109\/TNN.2004.841794.","journal-title":"IEEE Transactions on Neural Networks"},{"issue":"2","key":"1559_CR13","doi-asserted-by":"publisher","first-page":"380","DOI":"10.1109\/TEVC.2019.2918140","volume":"24","author":"Y Tian","year":"2020","unstructured":"Y. Tian, X. Zhang, C. Wang, Y. Jin. An evolutionary algorithm for large-scale sparse multiobjective optimization problems. IEEE Transactions on Evolutionary Computation, vol. 24, no. 2, pp. 380\u2013393, 2020. DOI: https:\/\/doi.org\/10.1109\/TEVC.2019.2918140.","journal-title":"IEEE Transactions on Evolutionary Computation"},{"issue":"6","key":"1559_CR14","doi-asserted-by":"publisher","first-page":"3115","DOI":"10.1109\/TCYB.2020.2979930","volume":"51","author":"Y Tian","year":"2021","unstructured":"Y. Tian, C. Lu, X. Zhang, K. C. Tan, Y. Jin. Solving large-scale multiobjective optimization problems with sparse optimal solutions via unsupervised neural networks. IEEE Transactions on Cybernetics, vol. 51, no. 6, pp. 3115\u20133128, 2021. DOI: https:\/\/doi.org\/10.1109\/TCYB.2020.2979930.","journal-title":"IEEE Transactions on Cybernetics"},{"issue":"7","key":"1559_CR15","doi-asserted-by":"publisher","first-page":"6784","DOI":"10.1109\/TCYB.2020.3041325","volume":"52","author":"Y Tian","year":"2022","unstructured":"Y. Tian, C. Lu, X. Zhang, F. Cheng, Y. Jin. A pattern mining-based evolutionary algorithm for large-scale sparse multiobjective optimization problems. IEEE Transactions on Cybernetics, vol. 52, no. 7, pp. 6784\u20136797, 2022. DOI: https:\/\/doi.org\/10.1109\/TCYB.2020.3041325.","journal-title":"IEEE Transactions on Cybernetics"},{"issue":"2","key":"1559_CR16","doi-asserted-by":"publisher","first-page":"1127","DOI":"10.1007\/s40747-021-00553-0","volume":"9","author":"Y Zhang","year":"2023","unstructured":"Y. Zhang, Y. Tian, X. Zhang. Improved SparseEA for sparse large-scale multi-objective optimization problems. Complex & Intelligent Systems, vol. 9, no. 2, pp. 1127\u20131142, 2023. DOI: https:\/\/doi.org\/10.1007\/s40747-021-00553-0.","journal-title":"Complex & Intelligent Systems"},{"key":"1559_CR17","doi-asserted-by":"publisher","first-page":"449","DOI":"10.1016\/j.ins.2023.02.062","volume":"631","author":"Y Zou","year":"2023","unstructured":"Y. Zou, Y. Liu, J. Zou, S. Yang, J. Zheng. An evolutionary algorithm based on dynamic sparse grouping for sparse large scale multiobjective optimization. Information Sciences, vol. 631, pp. 449\u2013467, 2023. DOI: https:\/\/doi.org\/10.1016\/j.ins.2023.02.062.","journal-title":"Information Sciences"},{"issue":"18","key":"1559_CR18","doi-asserted-by":"publisher","first-page":"21116","DOI":"10.1007\/s10489-023-04574-9","volume":"53","author":"M Gao","year":"2023","unstructured":"M. Gao, X. Feng, H. Yu, X. Li. An efficient evolutionary algorithm based on deep reinforcement learning for large-scale sparse multiobjective optimization. Applied Intelligence, vol. 53, no. 18, pp. 21116\u201321139, 2023. DOI: https:\/\/doi.org\/10.1007\/s10489-023-04574-9.","journal-title":"Applied Intelligence"},{"key":"1559_CR19","doi-asserted-by":"publisher","unstructured":"J. Jiang, F. Han, J. Wang, Q. Ling, H. Han, Y. Wang. A two-stage evolutionary algorithm for large-scale sparse multiobjective optimization problems. Swarm and Evolutionary Computation, vol. 72, Article number 101093, 2022. DOI: https:\/\/doi.org\/10.1016\/j.swevo.2022.101093.","DOI":"10.1016\/j.swevo.2022.101093"},{"issue":"11","key":"1559_CR20","doi-asserted-by":"publisher","first-page":"6989","DOI":"10.1109\/TSMC.2024.3446822","volume":"54","author":"Z Ding","year":"2024","unstructured":"Z. Ding, L. Chen, D. Sun, X. Zhang, W. Liu. Efficient sparse large-scale multiobjective optimization based on cross-scale knowledge fusion. IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 54, no. 11, pp. 6989\u20137001, 2024. DOI: https:\/\/doi.org\/10.1109\/TSMC.2024.3446822.","journal-title":"IEEE Transactions on Systems, Man, and Cybernetics: Systems"},{"issue":"5","key":"1559_CR21","doi-asserted-by":"publisher","first-page":"859","DOI":"10.1109\/TEVC.2021.3111209","volume":"26","author":"X Wang","year":"2022","unstructured":"X. Wang, K. Zhang, J. Wang, Y. Jin. An enhanced competitive swarm optimizer with strongly convex sparse operator for large-scale multiobjective optimization. IEEE Transactions on Evolutionary Computation, vol. 26, no. 5, pp. 859\u2013871, 2022. DOI: https:\/\/doi.org\/10.1109\/TEVC.2021.3111209.","journal-title":"IEEE Transactions on Evolutionary Computation"},{"key":"1559_CR22","doi-asserted-by":"publisher","first-page":"190","DOI":"10.1016\/j.neucom.2022.10.075","volume":"518","author":"Y Tian","year":"2023","unstructured":"Y. Tian, W. Zhu, X. Zhang, Y. Jin. A practical tutorial on solving optimization problems via PlatEMO. Neurocomputing, vol. 518, pp. 190\u2013205, 2023. DOI: https:\/\/doi.org\/10.1016\/j.neucom.2022.10.075.","journal-title":"Neurocomputing"},{"key":"1559_CR23","doi-asserted-by":"publisher","unstructured":"I. Kropp, A. P. Nejadhashemi, K. Deb. Benefits of sparse population sampling in multi-objective evolutionary computing for large-scale sparse optimization problems. Swarm and Evolutionary Computation, vol. 69, Article number 101025, 2022. DOI: https:\/\/doi.org\/10.1016\/j.swevo.2021.101025.","DOI":"10.1016\/j.swevo.2021.101025"},{"issue":"2","key":"1559_CR24","doi-asserted-by":"publisher","first-page":"460","DOI":"10.1109\/TEVC.2023.3256183","volume":"28","author":"I Kropp","year":"2024","unstructured":"I. Kropp, A. P. Nejadhashemi, K. Deb. Improved evolutionary operators for sparse large-scale multiobjective optimization problems. IEEE Transactions on Evolutionary Computation, vol. 28, no. 2, pp. 460\u2013473, 2024. DOI: https:\/\/doi.org\/10.1109\/TEVC.2023.3256183.","journal-title":"IEEE Transactions on Evolutionary Computation"},{"issue":"4","key":"1559_CR25","doi-asserted-by":"publisher","first-page":"68","DOI":"10.1109\/MCI.2011.942584","volume":"6","author":"J Zhang","year":"2011","unstructured":"J. Zhang, Z. H. Zhan, Y. Lin, N. Chen, Y. J. Gong, J. H. Zhong, H. S. H. Chung, Y. Li, Y. H. Shi. Evolutionary computation meets machine learning: A survey. IEEE Computational Intelligence Magazine, vol. 6, no. 4, pp. 68\u201375, 2011. DOI: https:\/\/doi.org\/10.1109\/MCI.2011.942584.","journal-title":"IEEE Computational Intelligence Magazine"},{"issue":"6","key":"1559_CR26","doi-asserted-by":"publisher","first-page":"1941","DOI":"10.1109\/TEVC.2023.3250350","volume":"27","author":"S Liu","year":"2023","unstructured":"S. Liu, Q. Lin, J. Li, K. C. Tan. A survey on learnable evolutionary algorithms for scalable multiobjective optimization. IEEE Transactions on Evolutionary Computation, vol. 27, no. 6, pp. 1941\u20131961, 2023. DOI: https:\/\/doi.org\/10.1109\/TEVC.2023.3250350.","journal-title":"IEEE Transactions on Evolutionary Computation"},{"issue":"6","key":"1559_CR27","doi-asserted-by":"publisher","first-page":"1794","DOI":"10.1109\/TEVC.2022.3232776","volume":"27","author":"Z H Zhan","year":"2023","unstructured":"Z. H. Zhan, J. Y. Li, S. Kwong, J. Zhang. Learning-aided evolution for optimization. IEEE Transactions on Evolutionary Computation, vol. 27, no. 6, pp. 1794\u20131808, 2023. DOI: https:\/\/doi.org\/10.1109\/TEVC.2022.3232776.","journal-title":"IEEE Transactions on Evolutionary Computation"},{"issue":"1","key":"1559_CR28","doi-asserted-by":"publisher","first-page":"16","DOI":"10.1109\/TEVC.2023.3278132","volume":"29","author":"Y Jiang","year":"2025","unstructured":"Y. Jiang, Z. H. Zhan, K. C. Tan, J. Zhang. Knowledge learning for evolutionary computation. IEEE Transactions on Evolutionary Computation, vol. 29, no. 1, pp. 16\u201330, 2025. DOI: https:\/\/doi.org\/10.1109\/TEVC.2023.3278132.","journal-title":"IEEE Transactions on Evolutionary Computation"},{"issue":"3","key":"1559_CR29","doi-asserted-by":"publisher","first-page":"456","DOI":"10.1109\/TEVC.2009.2033671","volume":"14","author":"Z Zhang","year":"2010","unstructured":"Z. Zhang, W. Liu, E. Tsang, B. Virginas. Expensive multiobjective optimization by MOEA\/D with Gaussian process model. IEEE Transactions on Evolutionary Computation, vol. 14, no. 3, pp. 456\u2013474, 2010. DOI: https:\/\/doi.org\/10.1109\/TEVC.2009.2033671.","journal-title":"IEEE Transactions on Evolutionary Computation"},{"issue":"2","key":"1559_CR30","doi-asserted-by":"publisher","first-page":"203","DOI":"10.1109\/TEVC.2018.2834881","volume":"23","author":"H Wang","year":"2019","unstructured":"H. Wang, Y. Jin, C. Sun, J. Doherty. Offline data-driven evolutionary optimization using selective surrogate ensembles. IEEE Transactions on Evolutionary Computation, vol. 23, no. 2, pp. 203\u2013216, 2019. DOI: https:\/\/doi.org\/10.1109\/TEVC.2018.2834881.","journal-title":"IEEE Transactions on Evolutionary Computation"},{"issue":"4","key":"1559_CR31","doi-asserted-by":"publisher","first-page":"572","DOI":"10.1109\/TEVC.2018.2874465","volume":"23","author":"H Ge","year":"2019","unstructured":"H. Ge, M. Zhao, L. Sun, Z. Wang, G. Tan, Q. Zhang, C. L. P. Chen. A many-objective evolutionary algorithm with two interacting processes: Cascade clustering and reference point incremental learning. IEEE Transactions on Evolutionary Computation, vol. 23, no. 4, pp. 572\u2013586, 2019. DOI: https:\/\/doi.org\/10.1109\/TEVC.2018.2874465.","journal-title":"IEEE Transactions on Evolutionary Computation"},{"key":"1559_CR32","doi-asserted-by":"publisher","unstructured":"Q. Liu, Y. Jin, M. Heiderich, T. Rodemann. Surrogateassisted evolutionary optimization of expensive many-objective irregular problems. Knowledge-Based Systems, vol. 240, Article number 108197, 2022. DOI: https:\/\/doi.org\/10.1016\/j.knosys.2022.108197.","DOI":"10.1016\/j.knosys.2022.108197"},{"issue":"5","key":"1559_CR33","doi-asserted-by":"publisher","first-page":"833","DOI":"10.1109\/TKDE.2018.2849727","volume":"31","author":"P Cui","year":"2019","unstructured":"P. Cui, X. Wang, J. Pei, W. Zhu. A survey on network embedding. IEEE Transactions on Knowledge and Data Engineering, vol. 31, no. 5, pp. 833\u2013852, 2019. DOI: https:\/\/doi.org\/10.1109\/TKDE.2018.2849727.","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"issue":"1","key":"1559_CR34","first-page":"54","volume":"1","author":"P Fournier-Viger","year":"2017","unstructured":"P. Fournier-Viger, J. C. W. Lin, R. U. Kiran, Y. S. Koh, R. Thomas. A survey of sequential pattern mining. Data Science and Pattern Recognition, vol. 1, no. 1, pp. 54\u201377, 2017.","journal-title":"Data Science and Pattern Recognition"},{"key":"1559_CR35","doi-asserted-by":"publisher","unstructured":"C. Zhuang, S. Yan, A. Nayebi, M. Schrimpf, M. C. Frank, J. J. DiCarlo, D. L. K. Yamins. Unsupervised neural network models of the ventral visual stream. Proceedings of the National Academy of Sciences of the United States of America, vol. 118, Article number 3, 2021. DOI: https:\/\/doi.org\/10.1073\/pnas.2014196118.","DOI":"10.1073\/pnas.2014196118"},{"key":"1559_CR36","doi-asserted-by":"publisher","first-page":"352","DOI":"10.1007\/978-3-540-30217-9_36","volume-title":"Proceedings of the 8th International Conference on Parallel Problem Solving from Nature","author":"J Ocenasek","year":"2004","unstructured":"J. Ocenasek, S. Kern, N. Hansen, P. Koumoutsakos. A mixed Bayesian optimization algorithm with variance adaptation. Proceedings of the 8th International Conference on Parallel Problem Solving from Nature, Springer, Birmingham, UK, pp. 352\u2013361, 2004. DOI: https:\/\/doi.org\/10.1007\/978-3-540-30217-9_36."},{"issue":"11","key":"1559_CR37","doi-asserted-by":"publisher","first-page":"3526","DOI":"10.1016\/j.asoc.2012.06.008","volume":"12","author":"Y Wang","year":"2012","unstructured":"Y. Wang, J. Xiang, Z. Cai. A regularity model-based multiobjective estimation of distribution algorithm with reducing redundant cluster operator. Applied Soft Computing, vol. 12, no. 11, pp. 3526\u20133538, 2012. DOI: https:\/\/doi.org\/10.1016\/j.asoc.2012.06.008.","journal-title":"Applied Soft Computing"},{"issue":"11","key":"1559_CR38","doi-asserted-by":"publisher","first-page":"139","DOI":"10.1145\/3422622","volume":"63","author":"I Goodfellow","year":"2020","unstructured":"I. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville, Y. Bengio. Generative adversarial networks. Communications of the ACM, vol. 63, no. 11, pp. 139\u2013144, 2020. DOI: https:\/\/doi.org\/10.1145\/3422622.","journal-title":"Communications of the ACM"},{"issue":"6","key":"1559_CR39","doi-asserted-by":"publisher","first-page":"3129","DOI":"10.1109\/TCYB.2020.2985081","volume":"51","author":"C He","year":"2021","unstructured":"C. He, S. Huang, R. Cheng, K. C. Tan, Y. Jin. Evolutionary multiobjective optimization driven by generative adversarial networks (GANs). IEEE Transactions on Cybernetics, vol. 51, no. 6, pp. 3129\u20133142, 2021. DOI: https:\/\/doi.org\/10.1109\/TCYB.2020.2985081.","journal-title":"IEEE Transactions on Cybernetics"},{"issue":"8","key":"1559_CR40","doi-asserted-by":"publisher","first-page":"4631","DOI":"10.1109\/TNNLS.2021.3113158","volume":"34","author":"Z Wang","year":"2023","unstructured":"Z. Wang, H. Hong, K. Ye, G. E. Zhang, M. Jiang, K. C. Tan. Manifold interpolation for large-scale multiobjective optimization via generative adversarial networks. IEEE Transactions on Neural Networks and Learning Systems, vol. 34, no. 8, pp. 4631\u20134645, 2023. DOI: https:\/\/doi.org\/10.1109\/TNNLS.2021.3113158.","journal-title":"IEEE Transactions on Neural Networks and Learning Systems"},{"key":"1559_CR41","doi-asserted-by":"publisher","unstructured":"Q. Dang, G. Zhang, L. Wang, S. Yang, T. Zhan. A generative adversarial networks model based evolutionary algorithm for multimodal multi-objective optimization. IEEE Transactions on Emerging Topics in Computational Intelligence, to be published. DOI: https:\/\/doi.org\/10.1109\/TETCI.2024.3397996.","DOI":"10.1109\/TETCI.2024.3397996"},{"key":"1559_CR42","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/SSCI.2017.8280974","volume-title":"Proceedings of Symposium Series on Computational Intelligence","author":"H Zille","year":"2017","unstructured":"H. Zille, S. Mostaghim. Comparison study of large-scale optimisation techniques on the LSMOP benchmark functions. In Proceedings of Symposium Series on Computational Intelligence, IEEE, Honolulu, USA, pp. 1\u20138, 2017. DOI: https:\/\/doi.org\/10.1109\/SSCI.2017.8280974."},{"issue":"1","key":"1559_CR43","doi-asserted-by":"publisher","first-page":"53","DOI":"10.1109\/MSP.2017.2765202","volume":"35","author":"A Creswell","year":"2018","unstructured":"A. Creswell, T. White, V. Dumoulin, K. Arulkumaran, B. Sengupta, A. A. Bharath. Generative adversarial networks: An overview. IEEE Signal Processing Magazine, vol. 35, no. 1, pp. 53\u201365, 2018. DOI: https:\/\/doi.org\/10.1109\/MSP.2017.2765202.","journal-title":"IEEE Signal Processing Magazine"},{"key":"1559_CR44","first-page":"2672","volume-title":"Proceedings of the 28th International Conference on Neural Information Processing Systems","author":"I J Goodfellow","year":"2014","unstructured":"I. J. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville, Y. Bengio. Generative adversarial nets. In Proceedings of the 28th International Conference on Neural Information Processing Systems, Montreal, Canada, pp. 2672\u20132680, 2014."},{"key":"1559_CR45","volume-title":"Adam: A method for stochastic optimization","author":"D P Kingma","year":"2014","unstructured":"D. P. Kingma, J. Ba. Adam: A method for stochastic optimization, [Online], Available: https:\/\/arxiv.org\/abs\/1412.6980, 2014."},{"issue":"2","key":"1559_CR46","doi-asserted-by":"publisher","first-page":"182","DOI":"10.1109\/4235.996017","volume":"6","author":"K Deb","year":"2002","unstructured":"K. Deb, A. Pratap, S. Agarwal, T. Meyarivan. A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Transactions on Evolutionary Computation, vol. 6, no. 2, pp. 182\u2013197, 2002. DOI: https:\/\/doi.org\/10.1109\/4235.996017.","journal-title":"IEEE Transactions on Evolutionary Computation"},{"key":"1559_CR47","doi-asserted-by":"publisher","unstructured":"O. I. Abiodun, A. Jantan, A. E. Omolara, K. V. Dada, N. A. Mohamed, H. Arshad. State-of-the-art in artificial neural network applications: A survey. Heliyon, vol. 4, Article number e00938, 2018. DOI: https:\/\/doi.org\/10.1016\/j.heliyon.2018.e00938.","DOI":"10.1016\/j.heliyon.2018.e00938"},{"issue":"8","key":"1559_CR48","doi-asserted-by":"publisher","first-page":"2133","DOI":"10.1080\/01431160802549278","volume":"30","author":"D Stathakis","year":"2009","unstructured":"D. Stathakis. How many hidden layers and nodes? International Journal of Remote Sensing, vol. 30, no. 8, pp. 2133\u20132147, 2009. DOI: https:\/\/doi.org\/10.1080\/01431160802549278.","journal-title":"International Journal of Remote Sensing"},{"key":"1559_CR49","series-title":"Technical Report 2018001","doi-asserted-by":"publisher","DOI":"10.13140\/RG.2.2.12568.70403","volume-title":"Problem Definitions and Evaluation Criteria for the CEC Special Session on Evolutionary Algorithms for Sparse Optimization","author":"J J Liang","year":"2018","unstructured":"J. J. Liang, M. Gong, H. Li, C. T. Yue, B. Y. Qu. Problem Definitions and Evaluation Criteria for the CEC Special Session on Evolutionary Algorithms for Sparse Optimization. Technical Report 2018001, Computational Intelligence Laboratory, Zhengzhou University, Zheng-zhou, China, 2018. DOI: https:\/\/doi.org\/10.13140\/RG.2.2.12568.70403."},{"issue":"2","key":"1559_CR50","doi-asserted-by":"publisher","first-page":"174","DOI":"10.1109\/TEVC.2003.810761","volume":"7","author":"P A N Bosman","year":"2003","unstructured":"P. A. N. Bosman, D. Thierens. The balance between proximity and diversity in multiobjective evolutionary algorithms. IEEE Transactions on Evolutionary Computation, vol. 7, no. 2, pp. 174\u2013188, 2003. DOI: https:\/\/doi.org\/10.1109\/TEVC.2003.810761.","journal-title":"IEEE Transactions on Evolutionary Computation"},{"issue":"4","key":"1559_CR51","doi-asserted-by":"publisher","first-page":"257","DOI":"10.1109\/4235.797969","volume":"3","author":"E Zitzler","year":"1999","unstructured":"E. Zitzler, L. Thiele. Multiobjective evolutionary algorithms: A comparative case study and the strength Pareto approach. IEEE Transactions on Evolutionary Computation, vol. 3, no. 4, pp. 257\u2013271, 1999. DOI: https:\/\/doi.org\/10.1109\/4235.797969.","journal-title":"IEEE Transactions on Evolutionary Computation"}],"container-title":["Machine Intelligence Research"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11633-025-1559-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11633-025-1559-z","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11633-025-1559-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,2]],"date-time":"2026-02-02T15:04:24Z","timestamp":1770044664000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11633-025-1559-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,2]]},"references-count":51,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2026,2]]}},"alternative-id":["1559"],"URL":"https:\/\/doi.org\/10.1007\/s11633-025-1559-z","relation":{},"ISSN":["2731-538X","2731-5398"],"issn-type":[{"value":"2731-538X","type":"print"},{"value":"2731-5398","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,2]]},"assertion":[{"value":"7 November 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"22 April 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 February 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The authors declared that they have no conflicts of interest to this work.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations of conflict of interest"}}]}}