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Original Articles

Intelligent dynamic control policies for serial production lines

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Pages 65-77 | Received 01 Apr 1999, Accepted 01 Mar 2000, Published online: 27 Apr 2007

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Read on this site (10)

Abderrazzak Sabri, Hamid Allaoui & Omar Souissi. (2023) Reinforcement learning and stochastic dynamic programming for jointly scheduling jobs and preventive maintenance on a single machine to minimise earliness-tardiness. International Journal of Production Research 0:0, pages 1-15.
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Manuel Schneckenreither, Stefan Haeussler & Christoph Gerhold. (2021) Order release planning with predictive lead times: a machine learning approach. International Journal of Production Research 59:11, pages 3285-3303.
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Gustavo Bagni, Moacir Godinho Filho, Matthias Thürer & Mark Stevenson. (2021) Systematic review and discussion of production control systems that emerged between 1999 and 2018. Production Planning & Control 32:7, pages 511-525.
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Yacob Khojasteh & Ryo Sato. (2015) Selection of a pull production control system in multi-stage production processes. International Journal of Production Research 53:14, pages 4363-4379.
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Rodrigo Reyes Levalle, Manuel Scavarda & Shimon Y. Nof. (2013) Collaborative production line control: Minimisation of throughput variability and WIP. International Journal of Production Research 51:23-24, pages 7289-7307.
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Helmut Nechansky. (2013) Issues of organizational cybernetics and viability beyond Beer’s viable systems model. International Journal of General Systems 42:8, pages 838-859.
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Jiao Wang, Xueping Li & Xiaoyan Zhu. (2012) Intelligent dynamic control of stochastic economic lot scheduling by agent-based reinforcement learning. International Journal of Production Research 50:16, pages 4381-4395.
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D.E. Koulouriotis, A.S. Xanthopoulos & V.D. Tourassis. (2010) Simulation optimisation of pull control policies for serial manufacturing lines and assembly manufacturing systems using genetic algorithms. International Journal of Production Research 48:10, pages 2887-2912.
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KIRAN KUMAR RAVULAPATI, JAIDEEP RAO & TAPASK. DAS. (2004) A reinforcement learning approach to stochastic business games. IIE Transactions 36:4, pages 373-385.
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JoseM. Framinan, PedroL. González & Rafael Ruiz-Usano. (2003) The CONWIP production control system: Review and research issues. Production Planning & Control 14:3, pages 255-265.
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Articles from other publishers (24)

Rafael Diaz & Ali Ardalan. (2023) Innovating in data-driven production environments: simulation analysis of Net-CONWIP priority rule. Industrial Management & Data Systems 123:5, pages 1569-1598.
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Carolina Saavedra Sueldo, Ivo Perez Colo, Mariano De Paula, Sebastián A. Villar & Gerardo G. Acosta. (2022) ROS-based architecture for fast digital twin development of smart manufacturing robotized systems. Annals of Operations Research 322:1, pages 75-99.
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Manuel Schneckenreither, Stefan Haeussler & Juanjo Peiró. (2022) Average reward adjusted deep reinforcement learning for order release planning in manufacturing. Knowledge-Based Systems 247, pages 108765.
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Yunyi Kang, Logan Mathesen, Giulia Pedrielli, Feng Ju & Loo Hay Lee. (2021) Multifidelity Modeling for Analysis and Optimization of Serial Production Lines. IEEE Transactions on Automatic Control 66:8, pages 3460-3474.
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Hubert Missbauer & Reha UzsoyHubert Missbauer & Reha Uzsoy. 2020. Production Planning with Capacitated Resources and Congestion. Production Planning with Capacitated Resources and Congestion 263 279 .
Manuel Schneckenreither & Stefan Haeussler. 2019. Machine Learning, Optimization, and Data Science. Machine Learning, Optimization, and Data Science 545 559 .
Rodrigo Reyes LevalleRodrigo Reyes Levalle. 2018. Resilience by Teaming in Supply Chains and Networks. Resilience by Teaming in Supply Chains and Networks 101 111 .
Yunyi Kang, Logan Mathesen, Giulia Pedrielli & Feng Ju. (2017) Multi-fidelity modeling for analysis of serial production lines. Multi-fidelity modeling for analysis of serial production lines.
Maria Drakaki & Panagiotis Tzionas. (2017) Manufacturing Scheduling Using Colored Petri Nets and Reinforcement Learning. Applied Sciences 7:2, pages 136.
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Rodrigo Reyes Levalle & Shimon Y. Nof. (2015) A resilience by teaming framework for collaborative supply networks. Computers & Industrial Engineering 90, pages 67-85.
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Shih-Fang Wong & Yu-Yong Zhang. (2014) A model of flow-shop production system planning using multiple criteria and multiple constraint levels ( MC 2 ) . Concurrent Engineering 22:2, pages 172-180.
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A.S. Xanthopoulos, D.E. Koulouriotis, V.D. Tourassis & D.M. Emiris. (2013) Intelligent controllers for bi-objective dynamic scheduling on a single machine with sequence-dependent setups. Applied Soft Computing 13:12, pages 4704-4717.
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Dimitrios E. Koulouriotis & Alexandros Xanthopoulos. 2013. Outsourcing Management for Supply Chain Operations and Logistics Service. Outsourcing Management for Supply Chain Operations and Logistics Service 134 149 .
Alexandros Xanthopoulos & Dimitrios E. Koulouriotis. 2013. Industrial Engineering. Industrial Engineering 643 662 .
Xueping Li, Jiao Wang & Rapinder Sawhney. (2012) Reinforcement learning for joint pricing, lead-time and scheduling decisions in make-to-order systems. European Journal of Operational Research 221:1, pages 99-109.
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Zhicong Zhang, Li Zheng, Na Li, Weiping Wang, Shouyan Zhong & Kaishun Hu. (2012) Minimizing mean weighted tardiness in unrelated parallel machine scheduling with reinforcement learning. Computers & Operations Research 39:7, pages 1315-1324.
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Rodrigo Reyes Levalle, Manuel Scavarda & Shimon Y. Nof. (2012) Collaborative production line control for collaborative supply networks. IFAC Proceedings Volumes 45:6, pages 487-492.
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Alexandros Xanthopoulos & Dimitrios E. Koulouriotis. 2011. Supply Chain Optimization, Design, and Management. Supply Chain Optimization, Design, and Management 212 231 .
Carlos D. Paternina-Arboleda, Jairo R. Montoya-Torres & Aldo Fabregas-Ariza. (2008) Simulation-optimization using a reinforcement learning approach. Simulation-optimization using a reinforcement learning approach.
Flávio Cesar Faria Fernandes & Moacir Godinho Filho. (2007) Sistemas de coordenação de ordens: revisão, classificação, funcionamento e aplicabilidade. Gestão & Produção 14:2, pages 337-352.
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Carlos D. Paternina-Arboleda & Tapas K. Das. (2005) A multi-agent reinforcement learning approach to obtaining dynamic control policies for stochastic lot scheduling problem. Simulation Modelling Practice and Theory 13:5, pages 389-406.
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Yi-Chi Wang & John M. Usher. (2005) Application of reinforcement learning for agent-based production scheduling. Engineering Applications of Artificial Intelligence 18:1, pages 73-82.
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Yi-Chi Wang & John M. Usher. (2004) Learning policies for single machine job dispatching. Robotics and Computer-Integrated Manufacturing 20:6, pages 553-562.
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D.C. Creighton & S. Nahavandi. (2002) The application of a reinforcement learning agent to a multi-product manufacturing facility. The application of a reinforcement learning agent to a multi-product manufacturing facility.

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