IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v193y2009i2p437-450.html
   My bibliography  Save this article

An algorithm for the maximum revenue jobshop problem

Author

Listed:
  • Penn, Michal
  • Raviv, Tal

Abstract

In this paper, we state and study the problem of selecting a product mix and a dispatching rule for a jobshop system to maximize its revenue rate over an infinite planning horizon. We solve the problem of obtaining maximum revenue by selecting a product mix and determine a schedule. The designed algorithm appropriately rounds an optimal solution to a fluid relaxation in which we replace discrete jobs with the flow of a continuous fluid. The algorithm solves the fluid relaxation optimally and then aims to keep the discrete schedule close to the continuous one obtained by the fluid solution. The schedule obtained is cyclic, with bounded WIP and asymptotically optimal. A secondary aim is to further reduce the WIP and the buffers' sizes by shortening the cycle length. This is achieved at the cost of a slight compromise on the revenue. We report on satisfactory computational results on some benchmark instances.

Suggested Citation

  • Penn, Michal & Raviv, Tal, 2009. "An algorithm for the maximum revenue jobshop problem," European Journal of Operational Research, Elsevier, vol. 193(2), pages 437-450, March.
    • Handle: RePEc:eee:ejores:v:193:y:2009:i:2:p:437-450
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377-2217(07)01138-1
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    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. Kamoun, H. & Sriskandarajah, C., 1993. "The complexity of scheduling jobs in repetitive manufacturing systems," European Journal of Operational Research, Elsevier, vol. 70(3), pages 350-364, November.
    2. Hanen, Claire, 1994. "Study of a NP-hard cyclic scheduling problem: The recurrent job-shop," European Journal of Operational Research, Elsevier, vol. 72(1), pages 82-101, January.
    3. J. G. Dai & Gideon Weiss, 2002. "A Fluid Heuristic for Minimizing Makespan in Job Shops," Operations Research, INFORMS, vol. 50(4), pages 692-707, August.
    4. Joseph Adams & Egon Balas & Daniel Zawack, 1988. "The Shifting Bottleneck Procedure for Job Shop Scheduling," Management Science, INFORMS, vol. 34(3), pages 391-401, March.
    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. Manzhan Gu & Xiwen Lu & Jinwei Gu, 2017. "An asymptotically optimal algorithm for large-scale mixed job shop scheduling to minimize the makespan," Journal of Combinatorial Optimization, Springer, vol. 33(2), pages 473-495, February.
    2. Jinwei Gu & Manzhan Gu & Xiwen Lu & Ying Zhang, 2018. "Asymptotically optimal policy for stochastic job shop scheduling problem to minimize makespan," Journal of Combinatorial Optimization, Springer, vol. 36(1), pages 142-161, July.

    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. Munier, A., 1996. "The complexity of a cyclic scheduling problem with identical machines and precedence constraints," European Journal of Operational Research, Elsevier, vol. 91(3), pages 471-480, June.
    2. Sels, Veronique & Craeymeersch, Kjeld & Vanhoucke, Mario, 2011. "A hybrid single and dual population search procedure for the job shop scheduling problem," European Journal of Operational Research, Elsevier, vol. 215(3), pages 512-523, December.
    3. Ganesan, Viswanath Kumar & Sivakumar, Appa Iyer, 2006. "Scheduling in static jobshops for minimizing mean flowtime subject to minimum total deviation of job completion times," International Journal of Production Economics, Elsevier, vol. 103(2), pages 633-647, October.
    4. Fowler, John W. & Mönch, Lars, 2022. "A survey of scheduling with parallel batch (p-batch) processing," European Journal of Operational Research, Elsevier, vol. 298(1), pages 1-24.
    5. Ramalhinho Lourenco, Helena, 1996. "Sevast'yanov's algorithm for the flow-shop scheduling problem," European Journal of Operational Research, Elsevier, vol. 91(1), pages 176-189, May.
    6. Taudes, Alfred & Trcka, Michael & Lukanowicz, Martin, 2002. "Organizational learning in production networks," Journal of Economic Behavior & Organization, Elsevier, vol. 47(2), pages 141-163, February.
    7. D J Stewardson & R I Whitfield, 2004. "A demonstration of the utility of fractional experimental design for finding optimal genetic algorithm parameter settings," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(2), pages 132-138, February.
    8. Liaw, Ching-Fang, 2000. "A hybrid genetic algorithm for the open shop scheduling problem," European Journal of Operational Research, Elsevier, vol. 124(1), pages 28-42, July.
    9. Rego, César & Duarte, Renato, 2009. "A filter-and-fan approach to the job shop scheduling problem," European Journal of Operational Research, Elsevier, vol. 194(3), pages 650-662, May.
    10. Bürgy, Reinhard & Bülbül, Kerem, 2018. "The job shop scheduling problem with convex costs," European Journal of Operational Research, Elsevier, vol. 268(1), pages 82-100.
    11. Zoghby, Jeriad & Wesley Barnes, J. & Hasenbein, John J., 2005. "Modeling the reentrant job shop scheduling problem with setups for metaheuristic searches," European Journal of Operational Research, Elsevier, vol. 167(2), pages 336-348, December.
    12. Sabuncuoglu, I. & Bayiz, M., 1999. "Job shop scheduling with beam search," European Journal of Operational Research, Elsevier, vol. 118(2), pages 390-412, October.
    13. Mukherjee, Saral & Chatterjee Ashis K, 2002. "Applying Machine Based Decomposition in 2-Machine Flow Shops," IIMA Working Papers WP2002-08-05, Indian Institute of Management Ahmedabad, Research and Publication Department.
    14. Jain, A. S. & Meeran, S., 1999. "Deterministic job-shop scheduling: Past, present and future," European Journal of Operational Research, Elsevier, vol. 113(2), pages 390-434, March.
    15. Guinet, Alain & Legrand, Marie, 1998. "Reduction of job-shop problems to flow-shop problems with precedence constraints," European Journal of Operational Research, Elsevier, vol. 109(1), pages 96-110, August.
    16. Idir Hamaz & Laurent Houssin & Sonia Cafieri, 2018. "A robust basic cyclic scheduling problem," EURO Journal on Computational Optimization, Springer;EURO - The Association of European Operational Research Societies, vol. 6(3), pages 291-313, September.
    17. Raúl Mencía & Carlos Mencía, 2021. "One-Machine Scheduling with Time-Dependent Capacity via Efficient Memetic Algorithms," Mathematics, MDPI, vol. 9(23), pages 1-24, November.
    18. Chen, Haoxun & Luh, Peter B., 2003. "An alternative framework to Lagrangian relaxation approach for job shop scheduling," European Journal of Operational Research, Elsevier, vol. 149(3), pages 499-512, September.
    19. Mehdi Mrad & Anis Gharbi & Mohamed Haouari & Mohamed Kharbeche, 2016. "An optimization-based heuristic for the machine reassignment problem," Annals of Operations Research, Springer, vol. 242(1), pages 115-132, July.
    20. Levner, Eugene & Kats, Vladimir & Levit, Vadim E., 1997. "An improved algorithm for cyclic flowshop scheduling in a robotic cell," European Journal of Operational Research, Elsevier, vol. 97(3), pages 500-508, March.

    More about this item

    Keywords

    Production Scheduling;

    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:eee:ejores:v:193:y:2009:i:2:p:437-450. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    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.