{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,11]],"date-time":"2025-09-11T18:48:58Z","timestamp":1757616538284,"version":"3.44.0"},"publisher-location":"Cham","reference-count":13,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031556838"},{"type":"electronic","value":"9783031556845"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"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":[],"published-print":{"date-parts":[[2024]]},"DOI":"10.1007\/978-3-031-55684-5_11","type":"book-chapter","created":{"date-parts":[[2024,5,21]],"date-time":"2024-05-21T06:01:47Z","timestamp":1716271307000},"page":"149-165","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Novel Decomposition-Based Multi-objective Evolutionary Algorithm Using Reinforcement Learning Adaptive Operator Selection (MOEA\/D-QL)"],"prefix":"10.1007","author":[{"given":"Jos\u00e9 Alfredo","family":"Brambila-Hern\u00e1ndez","sequence":"first","affiliation":[]},{"given":"Miguel \u00c1ngel","family":"Garc\u00eda-Morales","sequence":"additional","affiliation":[]},{"given":"H\u00e9ctor Joaqu\u00edn","family":"Fraire-Huacuja","sequence":"additional","affiliation":[]},{"given":"Laura","family":"Cruz-Reyes","sequence":"additional","affiliation":[]},{"given":"Juan","family":"Frausto-Sol\u00eds","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,5,22]]},"reference":[{"key":"11_CR1","doi-asserted-by":"crossref","unstructured":"Sun, L., Li, K.: Adaptive Operator Selection Based on Dynamic Thompson Sampling for MOEA\/D (Version 1). arXiv (2020)","DOI":"10.1007\/978-3-030-58115-2_19"},{"key":"11_CR2","doi-asserted-by":"crossref","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). Institute of Electrical and Electronics Engineers (IEEE)","DOI":"10.1109\/TEVC.2013.2239648"},{"key":"11_CR3","doi-asserted-by":"crossref","unstructured":"Fialho, \u00c1., da Costa, L., Schoenauer, M., Sebag, M.: Analyzing bandit-based adaptive operator selection mechanisms. Annals Math. Artif. Intell. 60(1), 25\u201364 (2010). Springer Verlag","DOI":"10.1007\/s10472-010-9213-y"},{"key":"11_CR4","doi-asserted-by":"crossref","unstructured":"Goldberg, D.E.: Probability matching, the magnitude of reinforcement, and classifier system bidding. Mach. Learn. 5(4), 407\u2013425 (1990). Springer Science and Business Media LLC","DOI":"10.1007\/BF00116878"},{"key":"11_CR5","doi-asserted-by":"crossref","unstructured":"Thierens, D.: An adaptive pursuit strategy for allocating operator probabilities. In: Proceedings of the 2005 Conference on Genetic and Evolutionary Computation\u2014GECCO \u201905. The 2005 Conference. ACM Press (2005)","DOI":"10.1145\/1068009.1068251"},{"key":"11_CR6","doi-asserted-by":"crossref","unstructured":"Auer, P., Cesa-Bianchi, N., Fischer, P.: Finite-time analysis of the multiarmed bandit problem. Mach. Learn. 47(2\/3), 235\u2013256 (2002). Springer Science and Business Media LLC","DOI":"10.1023\/A:1013689704352"},{"key":"11_CR7","volume-title":"Reinforcement Learning, Second Edition: An Introduction","author":"RS Sutton","year":"2018","unstructured":"Sutton, R.S., Barto, A.G.: Reinforcement Learning, Second Edition: An Introduction. MIT Press, London, England (2018)"},{"key":"11_CR8","unstructured":"Watkins, C.J.C.H.: Learning from Delayed Rewards. PhD Thesis, University of Cambridge, England (1989)"},{"issue":"6","key":"11_CR9","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)","journal-title":"IEEE Trans. Evol. Comput."},{"key":"11_CR10","doi-asserted-by":"publisher","DOI":"10.3929\/ETHZ-A-004284199","author":"K Deb","year":"2001","unstructured":"Deb, K., Thiele, L., Laumanns, M., Zitzler, E.: Scalable test problems for evolutionary multi-objective optimization. ETH Zurich (2001). https:\/\/doi.org\/10.3929\/ETHZ-A-004284199","journal-title":"ETH Zurich"},{"key":"11_CR11","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; special session on performance assessment of multi-objective optimization algorithms, technical report; University of Essex, Colchester. UK; Nanyang Technological University, Singapore, vol.  264, pp. 1\u201330 (2008)"},{"issue":"2","key":"11_CR12","doi-asserted-by":"publisher","first-page":"173","DOI":"10.1162\/106365600568202","volume":"8","author":"E Zitzler","year":"2000","unstructured":"Zitzler, E., Deb, K., Thiele, L.: Comparison of multiobjective evolutionary algorithms: empirical results. Evol. Comput. 8(2), 173\u2013195 (2000). https:\/\/doi.org\/10.1162\/106365600568202","journal-title":"Evol. Comput."},{"key":"11_CR13","doi-asserted-by":"crossref","unstructured":"Brambila-Hern\u00e1ndez, J.A., Garc\u00eda-Morales, M.\u00c1., Fraire-Huacuja, H.J., del Angel, A.B., Villegas-Huerta, E., Carbajal-L\u00f3pez, R.: Experimental evaluation of adaptive operators selection methods for the dynamic multiobjective evolutionary algorithm based on decomposition (DMOEA\/D). In: Castillo, O., Melin, P. (eds.) Hybrid Intelligent Systems Based on Extensions of Fuzzy Logic, Neural Networks and Metaheuristics. Studies in Computational Intelligence, vol. 1096. Springer, Cham (2023)","DOI":"10.1007\/978-3-031-28999-6_20"}],"container-title":["Studies in Computational Intelligence","New Horizons for Fuzzy Logic, Neural Networks and Metaheuristics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-55684-5_11","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,5]],"date-time":"2025-09-05T19:16:03Z","timestamp":1757099763000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-55684-5_11"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031556838","9783031556845"],"references-count":13,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-55684-5_11","relation":{},"ISSN":["1860-949X","1860-9503"],"issn-type":[{"type":"print","value":"1860-949X"},{"type":"electronic","value":"1860-9503"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"22 May 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}}]}}