{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,3]],"date-time":"2026-04-03T15:33:36Z","timestamp":1775230416695,"version":"3.50.1"},"reference-count":36,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Nature Science Foundation of China","doi-asserted-by":"publisher","award":["71931007"],"award-info":[{"award-number":["71931007"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Automat. Sci. Eng."],"published-print":{"date-parts":[[2025]]},"DOI":"10.1109\/tase.2024.3502521","type":"journal-article","created":{"date-parts":[[2024,11,27]],"date-time":"2024-11-27T14:51:36Z","timestamp":1732719096000},"page":"9190-9204","source":"Crossref","is-referenced-by-count":2,"title":["A Dynamic Joint Production-Service Scheduling Approach by a Model-and-Data Driven Algorithm"],"prefix":"10.1109","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9343-6019","authenticated-orcid":false,"given":"Yi-Lun","family":"Zhang","sequence":"first","affiliation":[{"name":"Department of Industrial and Management, Shanghai Jiao Tong University, Shanghai, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9241-0212","authenticated-orcid":false,"given":"Zhi-Bin","family":"Jiang","sequence":"additional","affiliation":[{"name":"Antai College of Economics and Management and the Data-Driven Management Decision Making Laboratory, Shanghai Jiao Tong University, Shanghai, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5243-6656","authenticated-orcid":false,"given":"Shan","family":"Jiang","sequence":"additional","affiliation":[{"name":"Johnson and Johnson Supply Chain, Bridgewater, NJ, USA"}]},{"given":"Li-Ping","family":"Zhou","sequence":"additional","affiliation":[{"name":"C. Y. Tung Institute of Intelligent Manufacturing and Service Management, Shanghai Jiao Tong University, Shanghai, China"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1080\/00207543.2017.1325528"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jclepro.2016.08.061"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TASE.2021.3054501"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1007\/s10696-012-9153-4"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1080\/07408170008967447"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1080\/24725854.2021.1957181"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejor.2017.01.012"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejor.2018.08.029"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1111\/poms.13407"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1287\/opre.1030.0087"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1080\/00207543.2021.2002963"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TASE.2020.2983061"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1080\/00207543.2020.1727041"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TASE.2022.3162653"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TASE.2021.3104716"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TASE.2020.3019567"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1016\/j.ress.2017.05.034"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1016\/j.cie.2019.04.055"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijpe.2017.07.008"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejor.2015.04.033"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1287\/opre.45.6.919"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1080\/00207543.2013.781282"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1287\/opre.45.1.42"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1287\/opre.44.4.634"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1287\/opre.48.5.709.12401"},{"issue":"3","key":"ref26","doi-asserted-by":"crossref","first-page":"957","DOI":"10.1016\/j.ejor.2018.12.025","article-title":"The joint transshipment and production control policies for multi-location production\/inventory systems","volume":"275","author":"Bhatnagar","year":"2019","journal-title":"Eur. J. Oper. Res."},{"issue":"16","key":"ref27","doi-asserted-by":"crossref","first-page":"4381","DOI":"10.1080\/00207543.2011.592158","article-title":"Intelligent dynamic control of stochastic economic lot scheduling by agent-based reinforcement learning","volume":"50","author":"Wang","year":"2012","journal-title":"Int. J. Prod. Res."},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1080\/00207543.2019.1662133"},{"issue":"16","key":"ref29","doi-asserted-by":"crossref","first-page":"5062","DOI":"10.1080\/00207543.2020.1748247","article-title":"Spatial arrangement using deep reinforcement learning to minimise rearrangement in ship block stockyards","volume":"58","author":"Kim","year":"2020","journal-title":"Int. J. Prod. Res."},{"key":"ref30","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1016\/j.cie.2017.05.026","article-title":"A reinforcement learning approach to parameter estimation in dynamic job shop scheduling","volume":"110","author":"Shahrabi","year":"2017","journal-title":"Comput. Ind. Eng."},{"issue":"13","key":"ref31","doi-asserted-by":"crossref","first-page":"3669","DOI":"10.1080\/00207540701846236","article-title":"Data-mining-based dynamic dispatching rule selection mechanism for shop floor control systems using a support vector machine approach","volume":"47","author":"Shiue","year":"2009","journal-title":"Int. J. Prod. Res."},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1080\/24725854.2022.2092918"},{"issue":"2","key":"ref33","doi-asserted-by":"crossref","first-page":"411","DOI":"10.1080\/00207549208942903","article-title":"Dynamic scheduling system utilizing machine learning as a knowledge acquisition tool","volume":"30","author":"Nakasuka","year":"1992","journal-title":"Int. J. Prod. Res."},{"issue":"4","key":"ref34","doi-asserted-by":"crossref","first-page":"444","DOI":"10.1080\/24725854.2019.1632502","article-title":"Applying deep learning to the newsvendor problem","volume":"52","author":"Oroojlooyjadid","year":"2019","journal-title":"IISE Trans."},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1080\/24725854.2021.1871687"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2022.3165757"}],"container-title":["IEEE Transactions on Automation Science and Engineering"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/8856\/10839176\/10767596.pdf?arnumber=10767596","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,24]],"date-time":"2026-03-24T19:51:27Z","timestamp":1774381887000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10767596\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"references-count":36,"URL":"https:\/\/doi.org\/10.1109\/tase.2024.3502521","relation":{},"ISSN":["1545-5955","1558-3783"],"issn-type":[{"value":"1545-5955","type":"print"},{"value":"1558-3783","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]}}}