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Integrated production and distribution scheduling with lifespan constraints

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  • Christian Viergutz
  • Sigrid Knust

Abstract

We consider an integrated production and distribution scheduling problem in a make-to-order business scenario. A product with a short lifespan (e.g., perishable or seasonal) is produced at a single production facility with a limited production rate. This means that the product expires in a constant time after its production is finished. Orders are received from a set of geographically dispersed customers, where a demand for the product and a time window for the delivery is associated with each customer for the planning period. A single vehicle with non-negligible traveling times between the locations is responsible for the deliveries. Due to the limited production and distribution resources, possibly not all customers may be supplied within their time windows or the lifespan. The problem consists in finding a selection of customers to be supplied such that the total satisfied demand is maximized. We extend the work by Armstrong et al. (Annals of Operations Research 159(1):395–414, 2008 ) on the problem for fixed delivery sequences by pointing out an error in their branch and bound algorithm and presenting a corrected variant. Furthermore, we introduce model extensions for handling delays of the production start as well as for variable production and distribution sequences. Efficient heuristic solution algorithms and computational results for randomly generated instances are presented. Copyright Springer Science+Business Media, LLC 2014

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  • Christian Viergutz & Sigrid Knust, 2014. "Integrated production and distribution scheduling with lifespan constraints," Annals of Operations Research, Springer, vol. 213(1), pages 293-318, February.
    • Handle: RePEc:spr:annopr:v:213:y:2014:i:1:p:293-318:10.1007/s10479-012-1197-z
    DOI: 10.1007/s10479-012-1197-z
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    Cited by:

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    2. Guo, Zhaoxia & Shi, Leyuan & Chen, Longchao & Liang, Yong, 2017. "A harmony search-based memetic optimization model for integrated production and transportation scheduling in MTO manufacturing," Omega, Elsevier, vol. 66(PB), pages 327-343.
    3. 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.
    4. 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.
    5. Azeddine Cheref & Alessandro Agnetis & Christian Artigues & Jean-Charles Billaut, 2017. "Complexity results for an integrated single machine scheduling and outbound delivery problem with fixed sequence," Journal of Scheduling, Springer, vol. 20(6), pages 681-693, December.
    6. Arda, Yasemin & Cattaruzza, Diego & François, Véronique & Ogier, Maxime, 2024. "Home chemotherapy delivery: An integrated production scheduling and multi-trip vehicle routing problem," European Journal of Operational Research, Elsevier, vol. 317(2), pages 468-486.
    7. 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.
    8. Sun, X.T. & Chung, S.H. & Chan, Felix T.S., 2015. "Integrated scheduling of a multi-product multi-factory manufacturing system with maritime transport limits," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 79(C), pages 110-127.
    9. 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.
    10. Sawik, Tadeusz, 2016. "Integrated supply, production and distribution scheduling under disruption risks," Omega, Elsevier, vol. 62(C), pages 131-144.
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