{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T04:03:16Z","timestamp":1743048196021,"version":"3.40.3"},"publisher-location":"Cham","reference-count":19,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783031242908"},{"type":"electronic","value":"9783031242915"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"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":[[2023]]},"DOI":"10.1007\/978-3-031-24291-5_31","type":"book-chapter","created":{"date-parts":[[2023,2,1]],"date-time":"2023-02-01T10:24:30Z","timestamp":1675247070000},"page":"395-406","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Reinforcement Learning Approach for Solving Integrated Mass Customization Process Planning and Job-Shop Scheduling Problem in a Reconfigurable Manufacturing System"],"prefix":"10.1007","author":[{"given":"Sini","family":"Gao","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Joanna","family":"Daaboul","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Julien","family":"Le Duigou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,2,2]]},"reference":[{"key":"31_CR1","doi-asserted-by":"publisher","first-page":"1394","DOI":"10.1016\/j.procir.2019.04.050","volume":"81","author":"S Aheleroff","year":"2019","unstructured":"Aheleroff, S., Philip, R., Zhong, R.Y., Xu, X.: The degree of mass personalisation under industry 4.0. Procedia CIRP 81, 1394\u20131399 (2019)","journal-title":"Procedia CIRP"},{"key":"31_CR2","doi-asserted-by":"publisher","unstructured":"Leng, J., et al.: Digital twin-driven rapid reconfiguration of the automated manufacturing system via an open architecture model. Robot. Comput. Integr. Manuf. 63 (2020).https:\/\/doi.org\/10.1016\/j.rcim.2019.101895","DOI":"10.1016\/j.rcim.2019.101895"},{"key":"31_CR3","doi-asserted-by":"publisher","first-page":"481","DOI":"10.1016\/j.jmsy.2021.03.001","volume":"59","author":"J Morgan","year":"2021","unstructured":"Morgan, J., Halton, M., Qiao, Y., Breslin, J.G.: Industry 4.0 smart reconfigurable manufacturing machines. J. Manuf. Syst. 59, 481\u2013506 (2021). https:\/\/doi.org\/10.1016\/j.jmsy.2021.03.001","journal-title":"J. Manuf. Syst."},{"issue":"2","key":"31_CR4","doi-asserted-by":"publisher","first-page":"121","DOI":"10.1007\/s11465-018-0483-0","volume":"13","author":"Y Koren","year":"2017","unstructured":"Koren, Y., Gu, X., Guo, W.: Reconfigurable manufacturing systems: principles, design, and future trends. Front. Mech. Eng. 13(2), 121\u2013136 (2017). https:\/\/doi.org\/10.1007\/s11465-018-0483-0","journal-title":"Front. Mech. Eng."},{"issue":"1","key":"31_CR5","doi-asserted-by":"publisher","first-page":"433","DOI":"10.1016\/S0007-8506(07)60138-3","volume":"54","author":"M Bruccoleri","year":"2005","unstructured":"Bruccoleri, M., Nigro, G.L., Perrone, G., Renna, P., Diega, S.N.L.: Production planning in reconfigurable enterprises and reconfigurable production systems. CIRP Ann. 54(1), 433\u2013436 (2005). https:\/\/doi.org\/10.1016\/S0007-8506(07)60138-3","journal-title":"CIRP Ann."},{"key":"31_CR6","doi-asserted-by":"publisher","first-page":"433","DOI":"10.1016\/j.ifacol.2019.11.097","volume":"52","author":"N Brahimi","year":"2019","unstructured":"Brahimi, N., Dolgui, A., Gurevsky, E., Yelles-Chaouche, A.R.: A literature review of optimization problems for reconfigurable manufacturing systems. IFAC-PapersOnLine 52, 433\u2013438 (2019). https:\/\/doi.org\/10.1016\/j.ifacol.2019.11.097","journal-title":"IFAC-PapersOnLine"},{"issue":"6","key":"31_CR7","doi-asserted-by":"publisher","first-page":"1531","DOI":"10.1007\/s10845-019-01531-7","volume":"31","author":"JP Usuga Cadavid","year":"2020","unstructured":"Usuga Cadavid, J.P., Lamouri, S., Grabot, B., Pellerin, R., Fortin, A.: Machine learning applied in production planning and control: a state-of-the-art in the era of industry 4.0. J. Intell. Manuf. 31(6), 1531\u20131558 (2020). https:\/\/doi.org\/10.1007\/s10845-019-01531-7","journal-title":"J. Intell. Manuf."},{"key":"31_CR8","doi-asserted-by":"crossref","unstructured":"Nassehi, A., Zhong, R.Y., Li, X., Epureanu, B.I.: Review of machine learning technologies and artificial intelligence in modern manufacturing systems. In: Design and Operation of Production Networks for Mass Personalization in the Era of Cloud Technology. pp. 317\u2013348. Elsevier Inc. (2022)","DOI":"10.1016\/B978-0-12-823657-4.00002-6"},{"key":"31_CR9","doi-asserted-by":"publisher","first-page":"104","DOI":"10.1016\/j.procir.2020.05.210","volume":"97","author":"C Kardos","year":"2021","unstructured":"Kardos, C., Laflamme, C., Gallina, V., Sihn, W.: Dynamic scheduling in a job-shop production system with reinforcement learning. Procedia CIRP 97, 104\u2013109 (2021)","journal-title":"Procedia CIRP"},{"key":"31_CR10","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.procir.2021.09.089","volume":"103","author":"J Tang","year":"2021","unstructured":"Tang, J., Salonitis, K.: A deep reinforcement learning based scheduling policy for reconfigurable manufacturing systems. Procedia CIRP 103, 1\u20137 (2021)","journal-title":"Procedia CIRP"},{"key":"31_CR11","doi-asserted-by":"publisher","first-page":"1198","DOI":"10.1016\/j.procir.2022.05.131","volume":"107","author":"J Tang","year":"2022","unstructured":"Tang, J., Haddad, Y., Salonitis, K.: Reconfigurable manufacturing system scheduling: a deep reinforcement learning approach. Procedia CIRP 107, 1198\u20131203 (2022). https:\/\/doi.org\/10.1016\/j.procir.2022.05.131","journal-title":"Procedia CIRP"},{"issue":"16","key":"31_CR12","doi-asserted-by":"publisher","first-page":"4936","DOI":"10.1080\/00207543.2021.1943037","volume":"60","author":"S Yang","year":"2021","unstructured":"Yang, S., Zhigang, Xu.: Intelligent scheduling and reconfiguration via deep reinforcement learning in smart manufacturing. Int. J. Prod. Res. 60(16), 4936\u20134953 (2021). https:\/\/doi.org\/10.1080\/00207543.2021.1943037","journal-title":"Int. J. Prod. Res."},{"issue":"9-10","key":"31_CR13","doi-asserted-by":"publisher","first-page":"5615","DOI":"10.1007\/s00170-021-08522-0","volume":"119","author":"AS Khan","year":"2021","unstructured":"Khan, A.S., Homri, L., Dantan, J.Y., Siadat, A.: An analysis of the theoretical and implementation aspects of process planning in a reconfigurable manufacturing system. Int. J. Adv. Manuf. Technol. 119(9\u201310), 5615\u20135646 (2021). https:\/\/doi.org\/10.1007\/s00170-021-08522-0","journal-title":"Int. J. Adv. Manuf. Technol."},{"key":"31_CR14","doi-asserted-by":"publisher","first-page":"1463","DOI":"10.1109\/TSMC.2020.3020732","volume":"52","author":"Y He","year":"2022","unstructured":"He, Y., Xing, L., Chen, Y., Pedrycz, W., Wang, L., Wu, G.: A generic Markov decision process model and reinforcement learning method for scheduling agile earth observation satellites. IEEE Trans. Syst. Man Cybern. Syst. 52, 1463\u20131474 (2022). https:\/\/doi.org\/10.1109\/TSMC.2020.3020732","journal-title":"IEEE Trans. Syst. Man Cybern. Syst."},{"key":"31_CR15","doi-asserted-by":"publisher","first-page":"279","DOI":"10.1007\/BF00992698","volume":"8","author":"CJCH Watkins","year":"1992","unstructured":"Watkins, C.J.C.H., Dayan, P.: Q-learning. Mach. Learn. 8, 279\u2013292 (1992). https:\/\/doi.org\/10.1007\/BF00992698","journal-title":"Mach. Learn."},{"key":"31_CR16","doi-asserted-by":"publisher","first-page":"279","DOI":"10.1146\/annurev-statistics-031219-041220","volume":"7","author":"J Clifton","year":"2020","unstructured":"Clifton, J., Laber, E.: Q-learning: theory and applications. Annu. Rev. Stat. Appl. 7, 279\u2013301 (2020). https:\/\/doi.org\/10.1146\/annurev-statistics-031219-041220","journal-title":"Annu. Rev. Stat. Appl."},{"key":"31_CR17","doi-asserted-by":"publisher","first-page":"110","DOI":"10.1016\/j.cirpj.2012.12.002","volume":"6","author":"A Azab","year":"2013","unstructured":"Azab, A., ElMaraghy, H., Nyhuis, P., Pachow-Frauenhofer, J., Schmidt, M.: Mechanics of change: a framework to reconfigure manufacturing systems. CIRP J. Manuf. Sci. Technol. 6, 110\u2013119 (2013). https:\/\/doi.org\/10.1016\/j.cirpj.2012.12.002","journal-title":"CIRP J. Manuf. Sci. Technol."},{"key":"31_CR18","doi-asserted-by":"publisher","first-page":"103244","DOI":"10.1016\/j.compind.2020.103244","volume":"120","author":"C Morariu","year":"2020","unstructured":"Morariu, C., Morariu, O., R\u0103ileanu, S., Borangiu, T.: Machine learning for predictive scheduling and resource allocation in large scale manufacturing systems. Comput. Ind. 120, 103244 (2020). https:\/\/doi.org\/10.1016\/j.compind.2020.103244","journal-title":"Comput. Ind."},{"key":"31_CR19","doi-asserted-by":"publisher","first-page":"13323","DOI":"10.3390\/su132313323","volume":"13","author":"S Gao","year":"2021","unstructured":"Gao, S., Daaboul, J., Le Duigou, J.: Process planning, scheduling, and layout optimization for multi-unit mass-customized products in sustainable reconfigurable manufacturing system. Sustainability 13, 13323 (2021). https:\/\/doi.org\/10.3390\/su132313323","journal-title":"Sustainability"}],"container-title":["Studies in Computational Intelligence","Service Oriented, Holonic and Multi-Agent Manufacturing Systems for Industry of the Future"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-24291-5_31","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,2,1]],"date-time":"2023-02-01T10:38:32Z","timestamp":1675247912000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-24291-5_31"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031242908","9783031242915"],"references-count":19,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-24291-5_31","relation":{},"ISSN":["1860-949X","1860-9503"],"issn-type":[{"type":"print","value":"1860-949X"},{"type":"electronic","value":"1860-9503"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"2 February 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"SOHOMA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Workshop on Service Orientation in Holonic and Multi-Agent Manufacturing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Bucharest","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Romania","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 September 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23 September 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"sohoma2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.sohoma22.cloud.upb.ro\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}