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A Benders decomposition-based heuristic for a production and outbound distribution scheduling problem with strict delivery constraints

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  • Kergosien, Y.
  • Gendreau, M.
  • Billaut, J.-C.

Abstract

The problem addressed in this paper is from a chemotherapy production and delivery environment, where production and delivery are strongly connected problems. Independent jobs have to be prepared by pharmacy technicians working in parallel. These jobs represent pouches of injectable chemotherapy preparations. The production process corresponds to a classic parallel machine scheduling problem. Then, the jobs must be delivered to the patients by a given due date. Only one person ensures all the deliveries, making several trips between the pharmacy production unit and the patient locations. We model this step as a multi-trip traveling salesman problem, where only one salesman can make more than one trip. The objective to minimize is the maximum tardiness of delivery. In addition to the constraints that link the two problems, some constraints related to the chemical stability of chemotherapy drugs have to be taken into account: The time between the production starting time and the date the treatment is administered to the patient (here, the delivery time) cannot exceed the stability duration, as the drug may otherwise become dangerous or ineffective for the patient. Due to these constraints, the problem is more difficult to solve. The proposed resolution method in this paper is a Benders decomposition-based heuristic that makes it possible to find feasible solutions and lower bounds. The advantage of the Benders decomposition approach is that this method exploits the structure of the problem, which can be easily decomposed into two stages. Computational experiments are conducted, and a comparison with a direct exact resolution shows the efficiency of this approach.

Suggested Citation

  • Kergosien, Y. & Gendreau, M. & Billaut, J.-C., 2017. "A Benders decomposition-based heuristic for a production and outbound distribution scheduling problem with strict delivery constraints," European Journal of Operational Research, Elsevier, vol. 262(1), pages 287-298.
  • Handle: RePEc:eee:ejores:v:262:y:2017:i:1:p:287-298
    DOI: 10.1016/j.ejor.2017.03.028
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    Cited by:

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    3. Véronique François & Yasemin Arda & Yves Crama, 2019. "Adaptive Large Neighborhood Search for Multitrip Vehicle Routing with Time Windows," Transportation Science, INFORMS, vol. 53(6), pages 1706-1730, November.
    4. Ling Liu & Sen Liu, 2020. "Integrated Production and Distribution Problem of Perishable Products with a Minimum Total Order Weighted Delivery Time," Mathematics, MDPI, vol. 8(2), pages 1-18, January.
    5. Hadid, Majed & Elomri, Adel & Mekkawy, Tarek El & Jouini, Oualid & Kerbache, Laoucine & Hamad, Anas, 2022. "Operations management of outpatient chemotherapy process: An optimization-oriented comprehensive review," Operations Research Perspectives, Elsevier, vol. 9(C).
    6. Alexis Robbes & Yannick Kergosien & Virginie André & Jean-Charles Billaut, 2022. "Efficient heuristics to minimize the total tardiness of chemotherapy drug production and delivery," Flexible Services and Manufacturing Journal, Springer, vol. 34(3), pages 785-820, September.
    7. Majed Hadid & Adel Elomri & Regina Padmanabhan & Laoucine Kerbache & Oualid Jouini & Abdelfatteh El Omri & Amir Nounou & Anas Hamad, 2022. "Clustering and Stochastic Simulation Optimization for Outpatient Chemotherapy Appointment Planning and Scheduling," IJERPH, MDPI, vol. 19(23), pages 1-34, November.
    8. Sun, X.T. & Chung, S.H. & Chan, Felix T.S. & Wang, Zheng, 2018. "The impact of liner shipping unreliability on the production–distribution scheduling of a decentralized manufacturing system," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 114(C), pages 242-269.
    9. Martha-Selene Casas-Ramírez & José-Fernando Camacho-Vallejo & Rosa G. González-Ramírez & José-Antonio Marmolejo-Saucedo & José-Manuel Velarde-Cantú, 2018. "Optimizing a Biobjective Production-Distribution Planning Problem Using a GRASP," Complexity, Hindawi, vol. 2018, pages 1-13, February.
    10. Witthayapraphakorn, Aphisak & Charnsethikul, Peerayuth, 2019. "Benders decomposition with special purpose method for the sub problem in lot sizing problem under uncertain demand," Operations Research Perspectives, Elsevier, vol. 6(C).
    11. Berghman, Lotte & Kergosien, Yannick & Billaut, Jean-Charles, 2023. "A review on integrated scheduling and outbound vehicle routing problems," European Journal of Operational Research, Elsevier, vol. 311(1), pages 1-23.
    12. Chevroton, Hugo & Kergosien, Yannick & Berghman, Lotte & Billaut, Jean-Charles, 2021. "Solving an integrated scheduling and routing problem with inventory, routing and penalty costs," European Journal of Operational Research, Elsevier, vol. 294(2), pages 571-589.
    13. Zhang, Jian & Nault, Barrie R. & Dimitrakopoulos, Roussos G., 2019. "Optimizing a mineral value chain with market uncertainty using benders decomposition," European Journal of Operational Research, Elsevier, vol. 274(1), pages 227-239.

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