IDEAS home Printed from https://ideas.repec.org/a/spr/joheur/v29y2023i1d10.1007_s10732-023-09509-8.html
   My bibliography  Save this article

Minimizing total completion time in large-sized pharmaceutical quality control scheduling

Author

Listed:
  • Miguel S. E. Martins

    (Universidade de Lisboa)

  • Joaquim L. Viegas

    (Universidade de Lisboa)

  • Tiago Coito

    (Universidade de Lisboa)

  • Bernardo Firme

    (Universidade de Lisboa)

  • Andrea Costigliola

    (Hovione Farmaciência, S.A.)

  • João Figueiredo

    (Universidade de Lisboa)

  • Susana M. Vieira

    (Universidade de Lisboa)

  • João M. C. Sousa

    (Universidade de Lisboa)

Abstract

This paper proposes an algorithm for the effective scheduling of analytical chemistry tests in the context of quality control for pharmaceutical manufacturing. The problem is formulated as an extension of a dual resource constrained flexible job shop scheduling problem for the allocation of both machines and analysts resources for analytical laboratory work of real dimensions. The formulation is novel and custom made to fit real quality control laboratory. The novelty comes from allowing multiple analyst interventions for each machine allocation while minimising the total completion time, formulated as a mixed integer linear programming model. A three-level dynamic heuristic is proposed to solve the problem efficiently for instances representative of real world schedules. The CPLEX solver and a Tabu Search algorithm are used for comparison. Results show that the heuristic is competitive with the other strategies for medium-sized instances while outperforming them for large-sized instances. The dynamic heuristic runs in a very short amount of time, making it suitable for real world environments. This work is valuable for the development of laboratory management solutions for quality control as it presents a way to provide automatic scheduling of resources.

Suggested Citation

  • Miguel S. E. Martins & Joaquim L. Viegas & Tiago Coito & Bernardo Firme & Andrea Costigliola & João Figueiredo & Susana M. Vieira & João M. C. Sousa, 2023. "Minimizing total completion time in large-sized pharmaceutical quality control scheduling," Journal of Heuristics, Springer, vol. 29(1), pages 177-206, February.
    • Handle: RePEc:spr:joheur:v:29:y:2023:i:1:d:10.1007_s10732-023-09509-8
    DOI: 10.1007/s10732-023-09509-8
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10732-023-09509-8
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10732-023-09509-8?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. Ho, Nhu Binh & Tay, Joc Cing & Lai, Edmund M.-K., 2007. "An effective architecture for learning and evolving flexible job-shop schedules," European Journal of Operational Research, Elsevier, vol. 179(2), pages 316-333, June.
    2. Dominik Kress & David Müller & Jenny Nossack, 2019. "A worker constrained flexible job shop scheduling problem with sequence-dependent setup times," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 41(1), pages 179-217, March.
    3. Haochen Zhang & Shaowei Cai & Chuan Luo & Minghao Yin, 2017. "An efficient local search algorithm for the winner determination problem," Journal of Heuristics, Springer, vol. 23(5), pages 367-396, October.
    4. Shen, Liji & Dauzère-Pérès, Stéphane & Neufeld, Janis S., 2018. "Solving the flexible job shop scheduling problem with sequence-dependent setup times," European Journal of Operational Research, Elsevier, vol. 265(2), pages 503-516.
    5. Luis Flores-Luyo & Agostinho Agra & Rosa Figueiredo & Eladio Ocaña, 2020. "Heuristics for a vehicle routing problem with information collection in wireless networks," Journal of Heuristics, Springer, vol. 26(2), pages 187-217, April.
    6. S. S. Panwalkar & Wafik Iskander, 1977. "A Survey of Scheduling Rules," Operations Research, INFORMS, vol. 25(1), pages 45-61, February.
    7. M. R. Garey & D. S. Johnson & Ravi Sethi, 1976. "The Complexity of Flowshop and Jobshop Scheduling," Mathematics of Operations Research, INFORMS, vol. 1(2), pages 117-129, May.
    8. Miguel R. Lopes & Andrea Costigliola & Rui Pinto & Susana Vieira & Joao M.C. Sousa, 2020. "Pharmaceutical quality control laboratory digital twin – A novel governance model for resource planning and scheduling," International Journal of Production Research, Taylor & Francis Journals, vol. 58(21), pages 6553-6567, November.
    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. Valls, Vicente & Angeles Perez, M. & Sacramento Quintanilla, M., 1998. "A tabu search approach to machine scheduling," European Journal of Operational Research, Elsevier, vol. 106(2-3), pages 277-300, April.
    2. Fátima Pilar & Eliana Costa e Silva & Ana Borges, 2023. "Optimizing Vehicle Repairs Scheduling Using Mixed Integer Linear Programming: A Case Study in the Portuguese Automobile Sector," Mathematics, MDPI, vol. 11(11), pages 1-23, June.
    3. 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.
    4. Helga Ingimundardottir & Thomas Philip Runarsson, 2018. "Discovering dispatching rules from data using imitation learning: A case study for the job-shop problem," Journal of Scheduling, Springer, vol. 21(4), pages 413-428, August.
    5. Yannik Zeiträg & José Rui Figueira, 2023. "Automatically evolving preference-based dispatching rules for multi-objective job shop scheduling," Journal of Scheduling, Springer, vol. 26(3), pages 289-314, June.
    6. Da Col, Giacomo & Teppan, Erich C., 2022. "Industrial-size job shop scheduling with constraint programming," Operations Research Perspectives, Elsevier, vol. 9(C).
    7. Shen, Liji & Dauzère-Pérès, Stéphane & Neufeld, Janis S., 2018. "Solving the flexible job shop scheduling problem with sequence-dependent setup times," European Journal of Operational Research, Elsevier, vol. 265(2), pages 503-516.
    8. González, Miguel A. & Vela, Camino R. & Varela, Ramiro, 2015. "Scatter search with path relinking for the flexible job shop scheduling problem," European Journal of Operational Research, Elsevier, vol. 245(1), pages 35-45.
    9. Berterottière, Lucas & Dauzère-Pérès, Stéphane & Yugma, Claude, 2024. "Flexible job-shop scheduling with transportation resources," European Journal of Operational Research, Elsevier, vol. 312(3), pages 890-909.
    10. Blazewicz, Jacek & Domschke, Wolfgang & Pesch, Erwin, 1996. "The job shop scheduling problem: Conventional and new solution techniques," European Journal of Operational Research, Elsevier, vol. 93(1), pages 1-33, August.
    11. Alper Türkyılmaz & Özlem Şenvar & İrem Ünal & Serol Bulkan, 2020. "A research survey: heuristic approaches for solving multi objective flexible job shop problems," Journal of Intelligent Manufacturing, Springer, vol. 31(8), pages 1949-1983, December.
    12. Wieslaw Kubiak & Yanling Feng & Guo Li & Suresh P. Sethi & Chelliah Sriskandarajah, 2020. "Efficient algorithms for flexible job shop scheduling with parallel machines," Naval Research Logistics (NRL), John Wiley & Sons, vol. 67(4), pages 272-288, June.
    13. Seyed Mahdi Homayouni & Dalila B. M. M. Fontes, 2021. "Production and transport scheduling in flexible job shop manufacturing systems," Journal of Global Optimization, Springer, vol. 79(2), pages 463-502, February.
    14. Drexl, Andreas & Kolisch, Rainer, 1991. "Produktionsplanung und -steuerung bei Einzel- und Kleinserienfertigung," Manuskripte aus den Instituten für Betriebswirtschaftslehre der Universität Kiel 281, Christian-Albrechts-Universität zu Kiel, Institut für Betriebswirtschaftslehre.
    15. Mehravaran, Yasaman & Logendran, Rasaratnam, 2012. "Non-permutation flowshop scheduling in a supply chain with sequence-dependent setup times," International Journal of Production Economics, Elsevier, vol. 135(2), pages 953-963.
    16. Lunardi, Willian T. & Birgin, Ernesto G. & Ronconi, Débora P. & Voos, Holger, 2021. "Metaheuristics for the online printing shop scheduling problem," European Journal of Operational Research, Elsevier, vol. 293(2), pages 419-441.
    17. Zhengcai Cao & Lijie Zhou & Biao Hu & Chengran Lin, 2019. "An Adaptive Scheduling Algorithm for Dynamic Jobs for Dealing with the Flexible Job Shop Scheduling Problem," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 61(3), pages 299-309, June.
    18. Seyed Habib A. Rahmati & Abbas Ahmadi & Kannan Govindan, 2018. "A novel integrated condition-based maintenance and stochastic flexible job shop scheduling problem: simulation-based optimization approach," Annals of Operations Research, Springer, vol. 269(1), pages 583-621, October.
    19. Shen, Liji & Buscher, Udo, 2012. "Solving the serial batching problem in job shop manufacturing systems," European Journal of Operational Research, Elsevier, vol. 221(1), pages 14-26.
    20. Rossi, Andrea, 2014. "Flexible job shop scheduling with sequence-dependent setup and transportation times by ant colony with reinforced pheromone relationships," International Journal of Production Economics, Elsevier, vol. 153(C), pages 253-267.

    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:joheur:v:29:y:2023:i:1:d:10.1007_s10732-023-09509-8. 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.