IDEAS home Printed from https://ideas.repec.org/a/taf/tprsxx/v54y2016i8p2419-2432.html
   My bibliography  Save this article

Production control in a complex production system using approximate dynamic programming

Author

Listed:
  • Han Wu
  • Gerald Evans
  • Ki-Hwan Bae

Abstract

Development of an efficient production and inventory control policy for a production system with multiple working stations, intermediate components and end products is difficult. In particular, uncertain demand and large changeover times at the work stations cause significant problems. In this paper, we consider an assembly line for dishwashers which require multiple types of wire racks that must be fabricated and coated at different work centres before supplying the assembly lines. An approximate dynamic programming (ADP) method is proposed to address the complexities associated with such a system. In addition, an Artificial Neural Network model is designed to approximate state values of the system, thus helping the system to make decisions at particular states. A near optimal production and inventory control policy is developed through an ADP algorithm. The proposed method can be extended to any similar system.

Suggested Citation

  • Han Wu & Gerald Evans & Ki-Hwan Bae, 2016. "Production control in a complex production system using approximate dynamic programming," International Journal of Production Research, Taylor & Francis Journals, vol. 54(8), pages 2419-2432, April.
    • Handle: RePEc:taf:tprsxx:v:54:y:2016:i:8:p:2419-2432
    DOI: 10.1080/00207543.2015.1086035
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00207543.2015.1086035
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/00207543.2015.1086035?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Candace Arai Yano & Ram Rachamadugu, 1991. "Sequencing to Minimize Work Overload in Assembly Lines with Product Options," Management Science, INFORMS, vol. 37(5), pages 572-586, May.
    2. David M. Markowitz & Lawrence M. Wein, 2001. "Heavy Traffic Analysis of Dynamic Cyclic Policies: A Unified Treatment of the Single Machine Scheduling Problem," Operations Research, INFORMS, vol. 49(2), pages 246-270, April.
    3. David M. Markowitz & Martin I. Reiman & Lawrence M. Wein, 2000. "The Stochastic Economic Lot Scheduling Problem: Heavy Traffic Analysis of Dynamic Cyclic Policies," Operations Research, INFORMS, vol. 48(1), pages 136-154, February.
    4. Robert C. Leachman & André Gascon, 1988. "A Heuristic Scheduling Policy for Multi-Item, Single-Machine Production Systems with Time-Varying, Stochastic Demands," Management Science, INFORMS, vol. 34(3), pages 377-390, March.
    5. Zhou, Bin & Zhao, Yao & Katehakis, Michael N., 2007. "Effective control policies for stochastic inventory systems with a minimum order quantity and linear costs," International Journal of Production Economics, Elsevier, vol. 106(2), pages 523-531, April.
    6. Robert C. Leachman & Zhong K. Xiong & André Gascon & Kwangtae Park, 1991. "Note: An Improvement to the Dynamic Cycle Lengths Heuristic for Scheduling the Multi-Item, Single-Machine," Management Science, INFORMS, vol. 37(9), pages 1201-1205, September.
    7. Winands, E.M.M. & Adan, I.J.B.F. & van Houtum, G.J., 2011. "The stochastic economic lot scheduling problem: A survey," European Journal of Operational Research, Elsevier, vol. 210(1), pages 1-9, April.
    8. Paul H. Zipkin, 1986. "Models for Design and Control of Stochastic, Multi-Item Batch Production Systems," Operations Research, INFORMS, vol. 34(1), pages 91-104, February.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Winands, E.M.M. & Adan, I.J.B.F. & van Houtum, G.J., 2011. "The stochastic economic lot scheduling problem: A survey," European Journal of Operational Research, Elsevier, vol. 210(1), pages 1-9, April.
    2. Lopez de Haro, Santiago & Gershwin, Stanley B. & Rosenfield, Donald B., 2009. "Schedule evaluation in unstable manufacturing environments," International Journal of Production Economics, Elsevier, vol. 121(1), pages 183-194, September.
    3. Germs, Remco & Van Foreest, Nicky D., 2011. "Admission policies for the customized stochastic lot scheduling problem with strict due-dates," European Journal of Operational Research, Elsevier, vol. 213(2), pages 375-383, September.
    4. Beemsterboer, Bart & Land, Martin & Teunter, Ruud, 2016. "Hybrid MTO-MTS production planning: An explorative study," European Journal of Operational Research, Elsevier, vol. 248(2), pages 453-461.
    5. Otis B. Jennings, 2008. "Heavy-Traffic Limits of Queueing Networks with Polling Stations: Brownian Motion in a Wedge," Mathematics of Operations Research, INFORMS, vol. 33(1), pages 12-35, February.
    6. Leven, Erik & Segerstedt, Anders, 2007. "A scheduling policy for adjusting economic lot quantities to a feasible solution," European Journal of Operational Research, Elsevier, vol. 179(2), pages 414-423, June.
    7. Sox, Charles R. & Jackson, Peter L. & Bowman, Alan & Muckstadt, John A., 1999. "A review of the stochastic lot scheduling problem," International Journal of Production Economics, Elsevier, vol. 62(3), pages 181-200, September.
    8. Smits, Sanne R. & Wagner, Michael & G. de Kok, Ton, 2004. "Determination of an order-up-to policy in the stochastic economic lot scheduling model," International Journal of Production Economics, Elsevier, vol. 90(3), pages 377-389, August.
    9. Donald D. Eisenstein, 2005. "Recovering Cyclic Schedules Using Dynamic Produce-Up-To Policies," Operations Research, INFORMS, vol. 53(4), pages 675-688, August.
    10. Kamath B, Narasimha & Bhattacharya, Subir, 2007. "Lead time minimization of a multi-product, single-processor system: A comparison of cyclic policies," International Journal of Production Economics, Elsevier, vol. 106(1), pages 28-40, March.
    11. Subba Rao, S. & Gunasekaran, A. & Goyal, S. K. & Martikainen, T., 1998. "Waiting line model applications in manufacturing," International Journal of Production Economics, Elsevier, vol. 54(1), pages 1-28, January.
    12. David M. Markowitz & Lawrence M. Wein, 2001. "Heavy Traffic Analysis of Dynamic Cyclic Policies: A Unified Treatment of the Single Machine Scheduling Problem," Operations Research, INFORMS, vol. 49(2), pages 246-270, April.
    13. Garn, Wolfgang & Aitken, James, 2015. "Agile factorial production for a single manufacturing line with multiple products," European Journal of Operational Research, Elsevier, vol. 245(3), pages 754-766.
    14. Sridhar Tayur, 2000. "Improving Operations and Quoting Accurate Lead Times in a Laminate Plant," Interfaces, INFORMS, vol. 30(5), pages 1-15, October.
    15. Beemsterboer, Bart & Land, Martin & Teunter, Ruud, 2017. "Flexible lot sizing in hybrid make-to-order/make-to-stock production planning," European Journal of Operational Research, Elsevier, vol. 260(3), pages 1014-1023.
    16. Wei-Min Lan & Tava Lennon Olsen, 2006. "Multiproduct Systems with Both Setup Times and Costs: Fluid Bounds and Schedules," Operations Research, INFORMS, vol. 54(3), pages 505-522, June.
    17. Alexey Matveev & Varvara Feoktistova & Ksenia Bolshakova, 2016. "On Global Near Optimality of Special Periodic Protocols for Fluid Polling Systems with Setups," Journal of Optimization Theory and Applications, Springer, vol. 171(3), pages 1055-1070, December.
    18. Wilhelm, W. E. & Som, Pradip, 1998. "Analysis of a single-stage, single-product, stochastic, MRP-controlled assembly system," European Journal of Operational Research, Elsevier, vol. 108(1), pages 74-93, July.
    19. S. Rajagopalan, 2002. "Make to Order or Make to Stock: Model and Application," Management Science, INFORMS, vol. 48(2), pages 241-256, February.
    20. Bautista, Joaquín & Alfaro, Rocío & Batalla, Cristina, 2015. "Modeling and solving the mixed-model sequencing problem to improve productivity," International Journal of Production Economics, Elsevier, vol. 161(C), pages 83-95.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:tprsxx:v:54:y:2016:i:8:p:2419-2432. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/TPRS20 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.