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Polynomial-time solvable cases of the capacitated multi-echelon shipping network scheduling problem with delivery deadlines

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  • Wang, Gang
  • Lei, Lei

Abstract

We consider the problem of operations scheduling for a capacitated multi-echelon shipping network with delivery deadlines. Over the network, semi-finished goods are shipped from origins to many demand points through a capacitated network consisting of shipping links and capacitated processing centers. The shipping operations are performed by a fleet of transporters which require time to travel from one location to another. Each demand point has a specified shipment quantity and a deadline for delivery. The problem is to find a feasible operation schedule to minimize the shipping and penalty cost. This problem is a computationally difficult one because of its inherent combinatorial nature. We report three polynomial-time solvable cases of this problem with (a) identical order quantities; (b) designated suppliers; and (c) divisible customer order sizes. These results reveal some interesting properties of the problem, and can be used to facilitate the design of fast heuristics for operations scheduling of capacitated shipping networks.

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  • Wang, Gang & Lei, Lei, 2012. "Polynomial-time solvable cases of the capacitated multi-echelon shipping network scheduling problem with delivery deadlines," International Journal of Production Economics, Elsevier, vol. 137(2), pages 263-271.
    • Handle: RePEc:eee:proeco:v:137:y:2012:i:2:p:263-271
    DOI: 10.1016/j.ijpe.2012.02.006
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    Cited by:

    1. Sawik, Tadeusz, 2014. "Joint supplier selection and scheduling of customer orders under disruption risks: Single vs. dual sourcing," Omega, Elsevier, vol. 43(C), pages 83-95.
    2. Gang Wang & Angappa Gunasekaran & Eric W. T. Ngai, 2018. "Distribution network design with big data: model and analysis," Annals of Operations Research, Springer, vol. 270(1), pages 539-551, November.
    3. Wang, Gang & Gunasekaran, Angappa, 2017. "Operations scheduling in reverse supply chains: Identical demand and delivery deadlines," International Journal of Production Economics, Elsevier, vol. 183(PB), pages 375-381.
    4. Jiang, Yuanchun & Shang, Jennifer & Liu, Yezheng, 2013. "Optimizing shipping-fee schedules to maximize e-tailer profits," International Journal of Production Economics, Elsevier, vol. 146(2), pages 634-645.
    5. Wang, Gang & Gunasekaran, Angappa & Ngai, Eric W.T. & Papadopoulos, Thanos, 2016. "Big data analytics in logistics and supply chain management: Certain investigations for research and applications," International Journal of Production Economics, Elsevier, vol. 176(C), pages 98-110.
    6. Sawik, Tadeusz, 2015. "On the fair optimization of cost and customer service level in a supply chain under disruption risks," Omega, Elsevier, vol. 53(C), pages 58-66.
    7. Gang Wang & Angappa Gunasekaran, 2017. "Modeling and analysis of sustainable supply chain dynamics," Annals of Operations Research, Springer, vol. 250(2), pages 521-536, March.
    8. Wang, Gang, 2024. "Order assignment and two-stage integrated scheduling in fruit and vegetable supply chains," Omega, Elsevier, vol. 124(C).

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