IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v159y2008i1p65-8210.1007-s10479-007-0280-3.html
   My bibliography  Save this article

An approach to predictive-reactive scheduling of parallel machines subject to disruptions

Author

Listed:
  • Alejandra Duenas
  • Dobrila Petrovic

Abstract

In this paper, a new predictive-reactive approach to a parallel machine scheduling problem in the presence of uncertain disruptions is presented. The approach developed is based on generating a predictive schedule that absorbs the effects of possible uncertain disruptions through adding idle times to the job processing times. The uncertain disruption considered is material shortage, described by the number of disruption occurrences and disruption repair period. These parameters are specified imprecisely and modelled using fuzzy sets. If the impact of a disruption is too high to be absorbed by the predictive schedule, a rescheduling action is carried out. This approach has been applied to solving a real-life scheduling problem of a pottery company. Copyright Springer Science+Business Media, LLC 2008

Suggested Citation

  • Alejandra Duenas & Dobrila Petrovic, 2008. "An approach to predictive-reactive scheduling of parallel machines subject to disruptions," Annals of Operations Research, Springer, vol. 159(1), pages 65-82, March.
    • Handle: RePEc:spr:annopr:v:159:y:2008:i:1:p:65-82:10.1007/s10479-007-0280-3
    DOI: 10.1007/s10479-007-0280-3
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10479-007-0280-3
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s10479-007-0280-3?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. Aytug, Haldun & Lawley, Mark A. & McKay, Kenneth & Mohan, Shantha & Uzsoy, Reha, 2005. "Executing production schedules in the face of uncertainties: A review and some future directions," European Journal of Operational Research, Elsevier, vol. 161(1), pages 86-110, February.
    2. S. S. Panwalkar & Wafik Iskander, 1977. "A Survey of Scheduling Rules," Operations Research, INFORMS, vol. 25(1), pages 45-61, February.
    3. Petrovic, Dobrila & Petrovic, Radivoj & Vujosevic, Mirko, 1996. "Fuzzy models for the newsboy problem," International Journal of Production Economics, Elsevier, vol. 45(1-3), pages 435-441, August.
    4. Li, Heng & Li, Zhicheng & Li, Ling X. & Hu, Bin, 2000. "A production rescheduling expert simulation system," European Journal of Operational Research, Elsevier, vol. 124(2), pages 283-293, July.
    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. Iwona Paprocka & Bożena Skołud, 2017. "A hybrid multi-objective immune algorithm for predictive and reactive scheduling," Journal of Scheduling, Springer, vol. 20(2), pages 165-182, April.
    2. Wang Hong Li & Liang Liang & Sonia Valeria Avilés-Sacoto & Raha Imanirad & Wade D. Cook & Joe Zhu, 2017. "Modeling efficiency in the presence of multiple partial input to output processes," Annals of Operations Research, Springer, vol. 250(1), pages 235-248, March.
    3. Guillermo Durand & Fernando Mele & J. Bandoni, 2012. "Determination of storage tanks location for optimal short-term scheduling in multipurpose/multiproduct batch-continuous plants under uncertainties," Annals of Operations Research, Springer, vol. 199(1), pages 225-247, October.

    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. Framinan, Jose M. & Ruiz, Rubén, 2010. "Architecture of manufacturing scheduling systems: Literature review and an integrated proposal," European Journal of Operational Research, Elsevier, vol. 205(2), pages 237-246, September.
    2. 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.
    3. Anurag Agarwal & Varghese S. Jacob & Hasan Pirkul, 2006. "An Improved Augmented Neural-Network Approach for Scheduling Problems," INFORMS Journal on Computing, INFORMS, vol. 18(1), pages 119-128, February.
    4. Binzi Xu & Kai Xu & Baolin Fei & Dengchao Huang & Liang Tao & Yan Wang, 2024. "Automatic Design of Energy-Efficient Dispatching Rules for Multi-Objective Dynamic Flexible Job Shop Scheduling Based on Dual Feature Weight Sets," Mathematics, MDPI, vol. 12(10), pages 1-24, May.
    5. Parlakturk, Ali & Kumar, Sunil, 2004. "Self-Interested Routing in Queueing Networks," Research Papers 1782r, Stanford University, Graduate School of Business.
    6. Faicel Hnaien & Taha Arbaoui, 2023. "Minimizing the makespan for the two-machine flow shop scheduling problem with random breakdown," Annals of Operations Research, Springer, vol. 328(2), pages 1437-1460, September.
    7. Gökçe Kiliçkaya & Tarik Küçükdeniz & Şakir Esnaf, 2021. "Fuzzy Clustering With Derivative–Free Search Algorithm for Location of Biogas Energy Systems," International Journal of Operations Research and Information Systems (IJORIS), IGI Global, vol. 12(4), pages 1-19, October.
    8. Lamas, Patricio & Goycoolea, Marcos & Pagnoncelli, Bernardo & Newman, Alexandra, 2024. "A target-time-windows technique for project scheduling under uncertainty," European Journal of Operational Research, Elsevier, vol. 314(2), pages 792-806.
    9. João M. C. Sousa & Rodrigo Luís & Rui Mirra Santos & Luís Mendonça & Susana M. Vieira, 2024. "Fuzzy Multi-Item Newsvendor Problem: An Application to Inventory Management," Mathematics, MDPI, vol. 12(11), pages 1-17, May.
    10. Ryu, Kwangyeol & Yücesan, Enver, 2010. "A fuzzy newsvendor approach to supply chain coordination," European Journal of Operational Research, Elsevier, vol. 200(2), pages 421-438, January.
    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. 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.
    13. Wang, John & Yan, Ruiliang & Hollister, Kimberly & Zhu, Dan, 2008. "A historic review of management science research in China," Omega, Elsevier, vol. 36(6), pages 919-932, December.
    14. 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.
    15. Monaci, Marta & Agasucci, Valerio & Grani, Giorgio, 2024. "An actor-critic algorithm with policy gradients to solve the job shop scheduling problem using deep double recurrent agents," European Journal of Operational Research, Elsevier, vol. 312(3), pages 910-926.
    16. Boysen, Nils & Briskorn, Dirk & Schwerdfeger, Stefan, 2019. "Matching supply and demand in a sharing economy: Classification, computational complexity, and application," European Journal of Operational Research, Elsevier, vol. 278(2), pages 578-595.
    17. 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.
    18. Han, Xiao-le & Lu, Zhi-qiang & Xi, Li-feng, 2010. "A proactive approach for simultaneous berth and quay crane scheduling problem with stochastic arrival and handling time," European Journal of Operational Research, Elsevier, vol. 207(3), pages 1327-1340, December.
    19. Zaumanis, Martins & Mallick, Rajib B. & Frank, Robert, 2014. "100% recycled hot mix asphalt: A review and analysis," Resources, Conservation & Recycling, Elsevier, vol. 92(C), pages 230-245.
    20. Gang Xuan & Win-Chin Lin & Shuenn-Ren Cheng & Wei-Lun Shen & Po-An Pan & Chih-Ling Kuo & Chin-Chia Wu, 2022. "A Robust Single-Machine Scheduling Problem with Two Job Parameter Scenarios," Mathematics, MDPI, vol. 10(13), pages 1-17, June.

    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:spr:annopr:v:159:y:2008:i:1:p:65-82:10.1007/s10479-007-0280-3. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.