IDEAS home Printed from https://ideas.repec.org/a/wly/navres/v56y2009i2p142-157.html
   My bibliography  Save this article

Production planning with resources subject to congestion

Author

Listed:
  • Jakob Asmundsson
  • Ronald L. Rardin
  • Can Hulusi Turkseven
  • Reha Uzsoy

Abstract

A fundamental difficulty in developing effective production planning models has been accurately reflecting the nonlinear dependency between workload and lead times. We develop a mathematical programming model for production planning in multiproduct, single stage systems that captures the nonlinear dependency between workload and lead times. We then use outer linearization of this nonlinear model to obtain a linear programming formulation and extend it to multistage systems. Extensive computational experiments validate the approach and compare its results to conventional models that assume workload‐independent planning lead times. © 2009 Wiley Periodicals, Inc. Naval Research Logistics, 2009

Suggested Citation

  • Jakob Asmundsson & Ronald L. Rardin & Can Hulusi Turkseven & Reha Uzsoy, 2009. "Production planning with resources subject to congestion," Naval Research Logistics (NRL), John Wiley & Sons, vol. 56(2), pages 142-157, March.
    • Handle: RePEc:wly:navres:v:56:y:2009:i:2:p:142-157
    DOI: 10.1002/nav.20335
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/nav.20335
    Download Restriction: no
    File URL: https://libkey.io/10.1002/nav.20335?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
    ---><---

    References listed on IDEAS

    as
    1. Srinivasan, A. & Carey, M. & Morton, T.E., 1988. "Resource Pricing And Aggregate Scheduling In Manufacturing Systems," GSIA Working Papers 88-89-58, Carnegie Mellon University, Tepper School of Business.
    2. Carson E. Agnew, 1976. "Dynamic Modeling and Control of Congestion-Prone Systems," Operations Research, INFORMS, vol. 24(3), pages 400-419, June.
    3. Lautenschläger, Matthias & Stadtler, H., 1998. "Modelling lead times depending on capacity utilization," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 9791, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    4. Byrne, M. D. & Bakir, M. A., 1999. "Production planning using a hybrid simulation - analytical approach," International Journal of Production Economics, Elsevier, vol. 59(1-3), pages 305-311, March.
    5. Kim, Bokang & Kim, Sooyoung, 2001. "Extended model for a hybrid production planning approach," International Journal of Production Economics, Elsevier, vol. 73(2), pages 165-173, September.
    6. Byrne, M.D. & Hossain, M.M., 2005. "Production planning: An improved hybrid approach," International Journal of Production Economics, Elsevier, vol. 93(1), pages 225-229, January.
    7. Markus Ettl & Gerald E. Feigin & Grace Y. Lin & David D. Yao, 2000. "A Supply Network Model with Base-Stock Control and Service Requirements," Operations Research, INFORMS, vol. 48(2), pages 216-232, April.
    8. Mark L. Spearman, 1991. "An Analytic Congestion Model for Closed Production Systems with IFR Processing Times," Management Science, INFORMS, vol. 37(8), pages 1015-1029, August.
    9. Stephen C. Graves, 1986. "A Tactical Planning Model for a Job Shop," Operations Research, INFORMS, vol. 34(4), pages 522-533, August.
    10. Steven T. Hackman & Robert C. Leachman, 1989. "A General Framework for Modeling Production," Management Science, INFORMS, vol. 35(4), pages 478-495, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Haeussler, S. & Stampfer, C. & Missbauer, H., 2020. "Comparison of two optimization based order release models with fixed and variable lead times," International Journal of Production Economics, Elsevier, vol. 227(C).
    2. Ghadimi, Foad & Aouam, Tarik & Haeussler, Stefan & Uzsoy, Reha, 2022. "Integrated and hierarchical systems for coordinating order acceptance and release planning," European Journal of Operational Research, Elsevier, vol. 303(3), pages 1277-1289.
    3. Manda, A.B. & Uzsoy, Reha, 2021. "Managing product transitions with learning and congestion effects," International Journal of Production Economics, Elsevier, vol. 239(C).
    4. Пигнастый, Олег, 2014. "Основы Статистической Теории Построения Континуальных Моделей Производственных Линий [Fundamentals Of The Statistical Theory Of The Construction Of Continuum Models Of Production Lines]," MPRA Paper 95240, University Library of Munich, Germany, revised 20 Aug 2014.
    5. Gopalswamy, Karthick & Uzsoy, Reha, 2021. "Conic programming models for production planning with clearing functions: Formulations and duality," European Journal of Operational Research, Elsevier, vol. 292(3), pages 953-966.
    6. Wen-Hsien Tsai & Yin-Hwa Lu, 2018. "A Framework of Production Planning and Control with Carbon Tax under Industry 4.0," Sustainability, MDPI, vol. 10(9), pages 1-24, September.
    7. Uday Venkatadri & Shentao Wang & Ashok Srinivasan, 2021. "A Model for Demand Planning in Supply Chains with Congestion Effects," Logistics, MDPI, vol. 5(1), pages 1-24, January.

    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. Julia Pahl & Stefan Voß & David Woodruff, 2007. "Production planning with load dependent lead times: an update of research," Annals of Operations Research, Springer, vol. 153(1), pages 297-345, September.
    2. Kefeli, Ali & Uzsoy, Reha & Fathi, Yahya & Kay, Michael, 2011. "Using a mathematical programming model to examine the marginal price of capacitated resources," International Journal of Production Economics, Elsevier, vol. 131(1), pages 383-391, May.
    3. Gopalswamy, Karthick & Uzsoy, Reha, 2021. "Conic programming models for production planning with clearing functions: Formulations and duality," European Journal of Operational Research, Elsevier, vol. 292(3), pages 953-966.
    4. Manda, A.B. & Uzsoy, Reha, 2021. "Managing product transitions with learning and congestion effects," International Journal of Production Economics, Elsevier, vol. 239(C).
    5. K. Taghizadeh & M. Bagherpour & I. Mahdavi, 2011. "An interactive fuzzy goal programming approach for multi-period multi-product production planning problem," Fuzzy Information and Engineering, Springer, vol. 3(4), pages 393-410, December.
    6. Missbauer, Hubert, 2011. "Order release planning with clearing functions: A queueing-theoretical analysis of the clearing function concept," International Journal of Production Economics, Elsevier, vol. 131(1), pages 399-406, May.
    7. Diaz, Juan Esteban & Handl, Julia & Xu, Dong-Ling, 2018. "Integrating meta-heuristics, simulation and exact techniques for production planning of a failure-prone manufacturing system," European Journal of Operational Research, Elsevier, vol. 266(3), pages 976-989.
    8. Ghadimi, Foad & Aouam, Tarik & Haeussler, Stefan & Uzsoy, Reha, 2022. "Integrated and hierarchical systems for coordinating order acceptance and release planning," European Journal of Operational Research, Elsevier, vol. 303(3), pages 1277-1289.
    9. Aouam, Tarik & Brahimi, Nadjib, 2013. "Integrated production planning and order acceptance under uncertainty: A robust optimization approach," European Journal of Operational Research, Elsevier, vol. 228(3), pages 504-515.
    10. Bilge Bilgen & Yelda Çelebi, 2013. "Integrated production scheduling and distribution planning in dairy supply chain by hybrid modelling," Annals of Operations Research, Springer, vol. 211(1), pages 55-82, December.
    11. Vasant, Pandian M. & Barsoum, Nader N. & Bhattacharya, Arijit, 2008. "Possibilistic optimization in planning decision of construction industry," International Journal of Production Economics, Elsevier, vol. 111(2), pages 664-675, February.
    12. Phillip O. Kriett & Sebastian Eirich & Martin Grunow, 2017. "Cycle time-oriented mid-term production planning for semiconductor wafer fabrication," International Journal of Production Research, Taylor & Francis Journals, vol. 55(16), pages 4662-4679, August.
    13. de Sampaio, Raimundo J.B. & Wollmann, Rafael R.G. & Vieira, Paula F.G., 2017. "A flexible production planning for rolling-horizons," International Journal of Production Economics, Elsevier, vol. 190(C), pages 31-36.
    14. Tien-Fu Liang, 2012. "Integrated manufacturing/distribution planning decisions with multiple imprecise goals in an uncertain environment," Quality & Quantity: International Journal of Methodology, Springer, vol. 46(1), pages 137-153, January.
    15. Tian, Feng & Willems, Sean P. & Kempf, Karl G., 2011. "An iterative approach to item-level tactical production and inventory planning," International Journal of Production Economics, Elsevier, vol. 133(1), pages 439-450, September.
    16. Haeussler, S. & Stampfer, C. & Missbauer, H., 2020. "Comparison of two optimization based order release models with fixed and variable lead times," International Journal of Production Economics, Elsevier, vol. 227(C).
    17. Missbauer, Hubert, 2009. "Models of the transient behaviour of production units to optimize the aggregate material flow," International Journal of Production Economics, Elsevier, vol. 118(2), pages 387-397, April.
    18. Rong Yuan & Stephen C. Graves, 2016. "Setting optimal production lot sizes and planned lead times in a job shop," International Journal of Production Research, Taylor & Francis Journals, vol. 54(20), pages 6105-6120, October.
    19. Pürgstaller, Peter & Missbauer, Hubert, 2012. "Rule-based vs. optimisation-based order release in workload control: A simulation study of a MTO manufacturer," International Journal of Production Economics, Elsevier, vol. 140(2), pages 670-680.
    20. Jaime Miranda & Pablo A. Rey & Antoine Sauré & Richard Weber, 2018. "Metro Uses a Simulation-Optimization Approach to Improve Fare-Collection Shift Scheduling," Interfaces, INFORMS, vol. 48(6), pages 529-542, November.

    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:wly:navres:v:56:y:2009:i:2:p:142-157. 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: Wiley Content Delivery (email available below). General contact details of provider: https://doi.org/10.1002/(ISSN)1520-6750 .

    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.