{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,2]],"date-time":"2026-04-02T15:26:37Z","timestamp":1775143597578,"version":"3.50.1"},"reference-count":23,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2018,7,4]],"date-time":"2018-07-04T00:00:00Z","timestamp":1530662400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61571346"],"award-info":[{"award-number":["61571346"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Prog Artif Intell"],"published-print":{"date-parts":[[2018,12]]},"DOI":"10.1007\/s13748-018-0155-7","type":"journal-article","created":{"date-parts":[[2018,7,4]],"date-time":"2018-07-04T10:25:06Z","timestamp":1530699906000},"page":"385-398","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Reinforcement learning aided parameter control in multi-objective evolutionary algorithm based on decomposition"],"prefix":"10.1007","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1677-2107","authenticated-orcid":false,"given":"Weikang","family":"Ning","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Baolong","family":"Guo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xinxing","family":"Guo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cheng","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yunyi","family":"Yan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2018,7,4]]},"reference":[{"issue":"2","key":"155_CR1","doi-asserted-by":"publisher","first-page":"174","DOI":"10.1109\/TEVC.2003.810761","volume":"7","author":"PAN Bosman","year":"2003","unstructured":"Bosman, P.A.N., Thierens, D.: The balance between proximity and diversity in multiobjective evolutionary algorithms. IEEE Trans. Evol. Comput. 7(2), 174\u2013188 (2003). https:\/\/doi.org\/10.1109\/TEVC.2003.810761","journal-title":"IEEE Trans. Evol. Comput."},{"issue":"10","key":"155_CR2","doi-asserted-by":"publisher","first-page":"3889","DOI":"10.1007\/s00500-016-2126-x","volume":"20","author":"PA Consoli","year":"2016","unstructured":"Consoli, P.A., Mei, Y., Minku, L.L., Yao, X.: Dynamic selection of evolutionary operators based on online learning and fitness landscape analysis. Soft. Comput. 20(10), 3889\u20133914 (2016)","journal-title":"Soft. Comput."},{"key":"155_CR3","doi-asserted-by":"crossref","unstructured":"Eiben, A.E., Horvath, M., Kowalczyk, W., Schut, M.C.: Reinforcement learning for online control of evolutionary algorithms. In: International Workshop on Engineering Self-Organising Applications, pp. 151\u2013160 (2006)","DOI":"10.1007\/978-3-540-69868-5_10"},{"issue":"5","key":"155_CR4","doi-asserted-by":"publisher","first-page":"692","DOI":"10.1109\/tevc.2010.2046173","volume":"15","author":"BM Ginley","year":"2011","unstructured":"Ginley, B.M., Maher, J., O\u2019Riordan, C., Morgan, F.: Maintaining healthy population diversity using adaptive crossover, mutation, and selection. IEEE Trans. Evol. Comput. 15(5), 692\u2013714 (2011). https:\/\/doi.org\/10.1109\/tevc.2010.2046173","journal-title":"IEEE Trans. Evol. Comput."},{"key":"155_CR5","first-page":"411","volume-title":"Lecture Notes in Computer Science","author":"Richard A. Gon\u00e7alves","year":"2015","unstructured":"Goncalves, R.A., Almeida, C.P., Pozo, A.: Upper confidence bound (UCB) algorithms for adaptive operator selection in MOEA\/D. In: Evolutionary Multi-criterion Optimization, Lecture Notes in Computer Science, pp. 411\u2013425. Springer, Cham (2015)"},{"key":"155_CR6","doi-asserted-by":"crossref","unstructured":"Karafotias, G., Eiben, A.E., Hoogendoorn, M.: Generic parameter control with reinforcement learning. In: Conference on Genetic and Evolutionary Computation, pp. 1319\u20131326 (2014)","DOI":"10.1145\/2576768.2598360"},{"issue":"2","key":"155_CR7","doi-asserted-by":"publisher","first-page":"167","DOI":"10.1109\/TEVC.2014.2308294","volume":"19","author":"G Karafotias","year":"2015","unstructured":"Karafotias, G., Hoogendoorn, M., Eiben, A.: Parameter control in evolutionary algorithms: trends and challenges. IEEE Trans. Evol. Comput. 19(2), 167\u2013187 (2015). https:\/\/doi.org\/10.1109\/TEVC.2014.2308294","journal-title":"IEEE Trans. Evol. Comput."},{"key":"155_CR8","doi-asserted-by":"crossref","first-page":"667","DOI":"10.1007\/978-3-319-16549-3_54","volume-title":"Applications of Evolutionary Computation","author":"Giorgos Karafotias","year":"2015","unstructured":"Karafotias, G., Hoogendoorn, M., Eiben, A.E.: Evaluating reward definitions for parameter control. In: European Conference on the Applications of Evolutionary Computation, pp. 667\u2013680 (2015)"},{"issue":"1","key":"155_CR9","doi-asserted-by":"publisher","first-page":"114","DOI":"10.1109\/TEVC.2013.2239648","volume":"18","author":"K Li","year":"2014","unstructured":"Li, K., Fialho, A., Kwong, S., Zhang, Q.: Adaptive operator selection with bandits for a multiobjective evolutionary algorithm based on decomposition. IEEE Trans. Evol. Comput. 18(1), 114\u2013130 (2014). https:\/\/doi.org\/10.1109\/TEVC.2013.2239648","journal-title":"IEEE Trans. Evol. Comput."},{"key":"155_CR10","doi-asserted-by":"publisher","first-page":"332","DOI":"10.1016\/j.ins.2015.12.022","volume":"339","author":"Q Lin","year":"2016","unstructured":"Lin, Q., Liu, Z., Yan, Q., Du, Z., Coello, C.A.C., Liang, Z., Wang, W., Chen, J.: Adaptive composite operator selection and parameter control for multiobjective evolutionary algorithm. Inf. Sci. 339, 332\u2013352 (2016). https:\/\/doi.org\/10.1016\/j.ins.2015.12.022","journal-title":"Inf. Sci."},{"key":"155_CR11","doi-asserted-by":"publisher","unstructured":"Muller, S.D., Schraudolph, N.N., Koumoutsakos, P.D.: Step size adaptation in evolution strategies using reinforcement learning. In: Proceedings of the World on Congress on Computational Intelligence, vol. 1, pp. 151\u2013156. IEEE Computer Society, Los Alamitos, CA, USA (2002). https:\/\/doi.org\/10.1109\/CEC.2002.1006225","DOI":"10.1109\/CEC.2002.1006225"},{"key":"155_CR12","doi-asserted-by":"crossref","unstructured":"Rost, A., Petrova, I., Buzdalova, A.: Adaptive parameter selection in evolutionary algorithms by reinforcement learning with dynamic discretization of parameter range. In: Genetic and Evolutionary Computation Conference Companion, pp. 141\u2013142 (2016)","DOI":"10.1145\/2908961.2908998"},{"key":"155_CR13","volume-title":"Reinforcement Learning: An Introduction","author":"R Sutton","year":"1998","unstructured":"Sutton, R., Barto, A.: Reinforcement Learning: An Introduction. MIT Press, Cambridge (1998)"},{"issue":"1","key":"155_CR14","doi-asserted-by":"publisher","first-page":"9","DOI":"10.1023\/A:1022633531479","volume":"3","author":"RS Sutton","year":"1988","unstructured":"Sutton, R.S.: Learning to predict by the methods of temporal differences. Mach. Learn. 3(1), 9\u201344 (1988). https:\/\/doi.org\/10.1023\/A:1022633531479","journal-title":"Mach. Learn."},{"issue":"127","key":"155_CR15","doi-asserted-by":"publisher","first-page":"65","DOI":"10.1016\/j.neucom.2013.06.043","volume":"127","author":"SM Venske","year":"2014","unstructured":"Venske, S.M., Gon\u00e7alves, R.A., Delgado, M.R.: ADEMO\/D: multiobjective optimization by an adaptive differential evolution algorithm. Neurocomputing 127(127), 65\u201377 (2014)","journal-title":"Neurocomputing"},{"issue":"8","key":"155_CR16","doi-asserted-by":"publisher","first-page":"506","DOI":"10.1007\/s00500-002-0235-1","volume":"7","author":"YY Wong","year":"2003","unstructured":"Wong, Y.Y., Lee, K.H., Leung, K.S., Ho, C.W.: A novel approach in parameter adaptation and diversity maintenance for genetic algorithms. Soft. Comput. 7(8), 506\u2013515 (2003)","journal-title":"Soft. Comput."},{"issue":"4","key":"155_CR17","doi-asserted-by":"publisher","first-page":"971","DOI":"10.1016\/j.ins.2007.09.026","volume":"178","author":"H Zhang","year":"2008","unstructured":"Zhang, H., Lu, J.: Adaptive evolutionary programming based on reinforcement learning. Inf. Sci. 178(4), 971\u2013984 (2008). https:\/\/doi.org\/10.1016\/j.ins.2007.09.026","journal-title":"Inf. Sci."},{"issue":"5","key":"155_CR18","doi-asserted-by":"publisher","first-page":"945","DOI":"10.1109\/TEVC.2009.2014613","volume":"13","author":"J Zhang","year":"2009","unstructured":"Zhang, J., Sanderson, A.C.: JADE: adaptive differential evolution with optional external archive. IEEE Trans. Evol. Comput. 13(5), 945\u2013958 (2009)","journal-title":"IEEE Trans. Evol. Comput."},{"issue":"6","key":"155_CR19","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.: MOEA\/D: a multiobjective evolutionary algorithm based on decomposition. IEEE Trans. Evol. Comput. 11(6), 712\u2013731 (2007). https:\/\/doi.org\/10.1109\/TEVC.2007.892759","journal-title":"IEEE Trans. Evol. Comput."},{"key":"155_CR20","doi-asserted-by":"publisher","unstructured":"Zhang, Q., Liu, W., Li, H.: The performance of a new version of MOEA\/D on CEC09 unconstrained MOP test instances. In: IEEE Congress on Evolutionary Computation, 2009. CEC \u201909, pp. 203\u2013208 (2009). https:\/\/doi.org\/10.1109\/CEC.2009.4982949","DOI":"10.1109\/CEC.2009.4982949"},{"key":"155_CR21","unstructured":"Zhang, Q., Zhou, A., Zhao, S., Suganthan, P.N., Liu, W., Tiwari, S.: Multiobjective optimization test instances for the CEC 2009 special session and competition. University of Essex, Colchester, UK and Nanyang Technological University, Singapore, Special Session on Performance Assessment of Multi-Objective Optimization Algorithms, Technical Report (2008)"},{"issue":"3","key":"155_CR22","doi-asserted-by":"publisher","first-page":"442","DOI":"10.1109\/TEVC.2011.2166159","volume":"16","author":"SZ Zhao","year":"2012","unstructured":"Zhao, S.Z., Suganthan, P., Zhang, Q.: Decomposition-based multiobjective evolutionary algorithm with an ensemble of neighborhood sizes. IEEE Trans. Evol. Comput. 16(3), 442\u2013446 (2012). https:\/\/doi.org\/10.1109\/TEVC.2011.2166159","journal-title":"IEEE Trans. Evol. Comput."},{"issue":"4","key":"155_CR23","doi-asserted-by":"publisher","first-page":"257","DOI":"10.1109\/4235.797969","volume":"3","author":"E Zitzler","year":"1999","unstructured":"Zitzler, E., Thiele, L.: Multiobjective evolutionary algorithms: a comparative case study and the strength Pareto approach. IEEE Trans. Evol. Comput. 3(4), 257\u2013271 (1999). https:\/\/doi.org\/10.1109\/4235.797969","journal-title":"IEEE Trans. Evol. Comput."}],"container-title":["Progress in Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s13748-018-0155-7\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s13748-018-0155-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s13748-018-0155-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,3]],"date-time":"2023-09-03T14:30:10Z","timestamp":1693751410000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s13748-018-0155-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,7,4]]},"references-count":23,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2018,12]]}},"alternative-id":["155"],"URL":"https:\/\/doi.org\/10.1007\/s13748-018-0155-7","relation":{},"ISSN":["2192-6352","2192-6360"],"issn-type":[{"value":"2192-6352","type":"print"},{"value":"2192-6360","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,7,4]]},"assertion":[{"value":"8 November 2017","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"25 June 2018","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"4 July 2018","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}