IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v199y2012i1p249-26810.1007-s10479-011-0954-8.html
   My bibliography  Save this article

Planning and scheduling of multistage multiproduct batch plants operating under production campaigns

Author

Listed:
  • Yanina Fumero
  • Gabriela Corsano
  • Jorge Montagna

Abstract

When plants are operated under stable conditions during reasonable time periods, operation with campaigns is particularly appropriate. The regular operation of the facilities simplifies the production control, the inventory management, the plant operability, etc. A campaign includes several batches of different products that are going to be manufactured and the same one is cyclically repeated over the time horizon. In this work, a mixed integer linear programming formulation is proposed for the planning and scheduling of given multiproduct batch plants operating with campaigns. The number and size of batches for each product, the campaign composition, the assignment of batches to units and their sequencing, and the number of times that the campaign is repeated over the time horizon must be determined. Taking into account this scenario, an appropriate performance measure is the minimization of the cycle time. An asynchronous slot-based continuous-time representation for modeling the assignment of batches to units and their sequencing is employed, and a novel rule for determining the maximum number of slots postulated for each unit is proposed. Copyright Springer Science+Business Media, LLC 2012

Suggested Citation

  • Yanina Fumero & Gabriela Corsano & Jorge Montagna, 2012. "Planning and scheduling of multistage multiproduct batch plants operating under production campaigns," Annals of Operations Research, Springer, vol. 199(1), pages 249-268, October.
    • Handle: RePEc:spr:annopr:v:199:y:2012:i:1:p:249-268:10.1007/s10479-011-0954-8
    DOI: 10.1007/s10479-011-0954-8
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10479-011-0954-8
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s10479-011-0954-8?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. Jose Pinto & Ignacio Grossmann, 1998. "Assignment and sequencing models for thescheduling of process systems," Annals of Operations Research, Springer, vol. 81(0), pages 433-466, June.
    2. Christodoulos Floudas & Xiaoxia Lin, 2005. "Mixed Integer Linear Programming in Process Scheduling: Modeling, Algorithms, and Applications," Annals of Operations Research, Springer, vol. 139(1), pages 131-162, October.
    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. Yanina Fumero & Gabriela Corsano & Jorge M. Montagna, 2017. "An MILP model for planning of batch plants operating in a campaign-mode," Annals of Operations Research, Springer, vol. 258(2), pages 415-435, November.

    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. Sumit Bose & Subir Bhattacharya, 2008. "A two pass heuristic algorithm for scheduling ‘blocked out’ units in continuous process industry," Annals of Operations Research, Springer, vol. 159(1), pages 293-313, March.
    2. Lara, Cristiana L. & Koenemann, Jochen & Nie, Yisu & de Souza, Cid C., 2023. "Scalable timing-aware network design via lagrangian decomposition," European Journal of Operational Research, Elsevier, vol. 309(1), pages 152-169.
    3. Casey Chung & Milind Dawande & Divakar Rajamani & Chelliah Sriskandarajah, 2011. "A Short-Range Scheduling Model for Blockbuster's Order-Processing Operation," Interfaces, INFORMS, vol. 41(5), pages 466-484, October.
    4. Christodoulos Floudas & Xiaoxia Lin, 2005. "Mixed Integer Linear Programming in Process Scheduling: Modeling, Algorithms, and Applications," Annals of Operations Research, Springer, vol. 139(1), pages 131-162, October.
    5. Farahmand, H. & Doorman, G.L., 2012. "Balancing market integration in the Northern European continent," Applied Energy, Elsevier, vol. 96(C), pages 316-326.
    6. Moo-Sung Sohn & Jiwoong Choi & Hoseog Kang & In-Chan Choi, 2017. "Multiobjective Production Planning at LG Display," Interfaces, INFORMS, vol. 47(4), pages 279-291, August.
    7. Philip Doganis & Haralambos Sarimveis, 2008. "Optimal production scheduling for the dairy industry," Annals of Operations Research, Springer, vol. 159(1), pages 315-331, March.
    8. Grzegorz Bocewicz & Zbigniew Banaszak & Izabela Nielsen, 2019. "Multimodal processes prototyping subject to grid-like network and fuzzy operation time constraints," Annals of Operations Research, Springer, vol. 273(1), pages 561-585, February.
    9. Alix Vargas & Carmen Fuster & David Corne, 2020. "Towards Sustainable Collaborative Logistics Using Specialist Planning Algorithms and a Gain-Sharing Business Model: A UK Case Study," Sustainability, MDPI, vol. 12(16), pages 1-29, August.
    10. Torres, Nelson & Greivel, Gus & Betz, Joshua & Moreno, Eduardo & Newman, Alexandra & Thomas, Brian, 2024. "Optimizing steel coil production schedules under continuous casting and hot rolling," European Journal of Operational Research, Elsevier, vol. 314(2), pages 496-508.
    11. Shehadeh, Karmel S. & Cohn, Amy E.M. & Epelman, Marina A., 2019. "Analysis of models for the Stochastic Outpatient Procedure Scheduling Problem," European Journal of Operational Research, Elsevier, vol. 279(3), pages 721-731.
    12. Gian Paramo & Arturo Bretas, 2023. "Proactive Frequency Stability Scheme: A Distributed Framework Based on Particle Filters and Synchrophasors," Energies, MDPI, vol. 16(11), pages 1-19, June.
    13. Mohammad Heydari & Kin Keung Lai, 2023. "Post-COVID-19 Pandemic Era and Sustainable Healthcare: Organization and Delivery of Health Economics Research (Principles and Clinical Practice)," Mathematics, MDPI, vol. 11(16), pages 1-30, August.
    14. Khayyam, Hamid & Naebe, Minoo & Bab-Hadiashar, Alireza & Jamshidi, Farshid & Li, Quanxiang & Atkiss, Stephen & Buckmaster, Derek & Fox, Bronwyn, 2015. "Stochastic optimization models for energy management in carbonization process of carbon fiber production," Applied Energy, Elsevier, vol. 158(C), pages 643-655.
    15. Ioannis Fragkos & Bert De Reyck, 2016. "Improving the Maritime Transshipment Operations of the Noble Group," Interfaces, INFORMS, vol. 46(3), pages 203-217, April.
    16. Chung, S.H. & Lau, H.C.W. & Choy, K.L. & Ho, G.T.S. & Tse, Y.K., 2010. "Application of genetic approach for advanced planning in multi-factory environment," International Journal of Production Economics, Elsevier, vol. 127(2), pages 300-308, October.
    17. Bohle, Carlos & Maturana, Sergio & Vera, Jorge, 2010. "A robust optimization approach to wine grape harvesting scheduling," European Journal of Operational Research, Elsevier, vol. 200(1), pages 245-252, January.
    18. Pulluru, Sai Jishna & Akkerman, Renzo, 2018. "Water-integrated scheduling of batch process plants: Modelling approach and application in technology selection," European Journal of Operational Research, Elsevier, vol. 269(1), pages 227-243.
    19. M. Saqlain & S. Ali & J. Y. Lee, 2023. "A Monte-Carlo tree search algorithm for the flexible job-shop scheduling in manufacturing systems," Flexible Services and Manufacturing Journal, Springer, vol. 35(2), pages 548-571, June.
    20. Laing, Harry & O'Malley, Chris & Browne, Anthony & Rutherford, Tony & Baines, Tony & Moore, Andrew & Black, Ken & Willis, Mark J., 2022. "Optimisation of energy usage and carbon emissions monitoring using MILP for an advanced anaerobic digester plant," Energy, Elsevier, vol. 256(C).

    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:199:y:2012:i:1:p:249-268:10.1007/s10479-011-0954-8. 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.