IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v159y2008i1p293-31310.1007-s10479-007-0265-2.html
   My bibliography  Save this article

A two pass heuristic algorithm for scheduling ‘blocked out’ units in continuous process industry

Author

Listed:
  • Sumit Bose
  • Subir Bhattacharya

Abstract

This paper addresses the problem of scheduling cascaded ‘blocked out’ continuous processing units separated by finite capacity storage tanks. The raw materials for the product lines arrive simultaneously on the input side of the first unit. But every unit can process only one product line at a time, thus giving rise to the possibility of spillage of raw material due to limited storage capacity. The need to process multiple product lines and the added constraint of multiple intermediate upliftment dates aggravate the problem. This problem is quite common in petrochemical industry. The paper provides a MINLP (Mixed Integer Non-Linear Programming) formulation of the problem. However, for any realistic scheduling horizon, the size of the problem is too large to be solved by standard packages. We have proposed a depth first branch and bound algorithm, guided by heuristics, to help planners in tackling the problem. The suggested algorithm could output near optimal solutions for scheduling horizons of 30 time periods when applied to real life situations involving 3 units and 3 product lines. Copyright Springer Science+Business Media, LLC 2008

Suggested Citation

  • 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.
    • Handle: RePEc:spr:annopr:v:159:y:2008:i:1:p:293-313:10.1007/s10479-007-0265-2
    DOI: 10.1007/s10479-007-0265-2
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10479-007-0265-2
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s10479-007-0265-2?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. Frauendorfer, K. & Konigsperger, E., 1996. "Concepts for improving scheduling decisions: An application in the chemical industry," International Journal of Production Economics, Elsevier, vol. 46(1), pages 27-38, December.
    3. 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.
    4. Siqun Wang & Monique Guignard, 2002. "Redefining Event Variables for Efficient Modeling of Continuous-Time Batch Processing," Annals of Operations Research, Springer, vol. 116(1), pages 113-126, October.
    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. 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.
    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.
    3. 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.
    4. 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.
    5. Bhattacharya, Subir & Bose, Sumit Kumar, 2007. "Mathematical model for scheduling operations in cascaded continuous processing units," European Journal of Operational Research, Elsevier, vol. 182(1), pages 1-14, October.
    6. Li, Nianqi & Klemeš, Jiří Jaromír & Sunden, Bengt & Wu, Zan & Wang, Qiuwang & Zeng, Min, 2022. "Heat exchanger network synthesis considering detailed thermal-hydraulic performance: Methods and perspectives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    7. Monkman, Susan K. & Morrice, Douglas J. & Bard, Jonathan F., 2008. "A production scheduling heuristic for an electronics manufacturer with sequence-dependent setup costs," European Journal of Operational Research, Elsevier, vol. 187(3), pages 1100-1114, June.
    8. Farahmand, H. & Doorman, G.L., 2012. "Balancing market integration in the Northern European continent," Applied Energy, Elsevier, vol. 96(C), pages 316-326.
    9. Abdelrahman Hosny & Sherief Reda, 2024. "Automatic MILP solver configuration by learning problem similarities," Annals of Operations Research, Springer, vol. 339(1), pages 909-936, August.
    10. Stefansson, Hlynur & Sigmarsdottir, Sigrun & Jensson, Pall & Shah, Nilay, 2011. "Discrete and continuous time representations and mathematical models for large production scheduling problems: A case study from the pharmaceutical industry," European Journal of Operational Research, Elsevier, vol. 215(2), pages 383-392, December.
    11. 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.
    12. Mancuso, A. & Compare, M. & Salo, A. & Zio, E., 2021. "Optimal Prognostics and Health Management-driven inspection and maintenance strategies for industrial systems," Reliability Engineering and System Safety, Elsevier, vol. 210(C).
    13. Philip Doganis & Haralambos Sarimveis, 2008. "Optimal production scheduling for the dairy industry," Annals of Operations Research, Springer, vol. 159(1), pages 315-331, March.
    14. Dujardin, Yann & Vanderpooten, Daniel & Boillot, Florence, 2015. "A multi-objective interactive system for adaptive traffic control," European Journal of Operational Research, Elsevier, vol. 244(2), pages 601-610.
    15. 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.
    16. Mohammad Heydari & Yanan Fan & Kin Keung Lai, 2023. "A Robust Site Selection Model under uncertainty for Special Hospital Wards in Hong Kong," Papers 2307.11508, arXiv.org.
    17. 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.
    18. 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.
    19. 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.
    20. Joey Huchette & Joey Huchette, 2019. "A Combinatorial Approach for Small and Strong Formulations of Disjunctive Constraints," Mathematics of Operations Research, INFORMS, vol. 44(3), pages 793-820, August.

    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:293-313:10.1007/s10479-007-0265-2. 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.