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Integrated Production, Inventory and Delivery Problems: Complexity and Algorithms

Author

Listed:
  • Feng Li

    (Institute of Industrial Engineering and Logistics Optimization, Northeastern University, Shenyang, 110819, China)

  • Zhi-Long Chen

    (Robert H. Smith School of Business, University of Maryland, College Park, Maryland 20742)

  • Zhi-Long Chen

    (Institute of Industrial Engineering and Logistics Optimization, Northeastern University, Shenyang, 110819, China)

Abstract

We consider several integrated production, inventory, and delivery problems that arise in a number of practical settings where customer orders have pre-specified delivery time windows. These orders are first processed in a plant and then delivered to the customers by transporters (such as trains and air flights) which have fixed delivery departure times. If an order is completed but not immediately delivered by a transporter, the order is kept temporarily in inventory, which incurs an inventory cost. There is a delivery cost for delivering an order, which varies with the departure time. Given a set of orders, the objective is to find an integrated schedule for processing the orders, keeping finished orders in inventory if necessary, and delivering them to the customers such that the total inventory and delivery cost is minimum. We consider two classes of problems: where order delivery is splittable and where order delivery is nonsplittable. For each of the problems considered, we study its computational complexity by either showing that the problem is NP-hard or proposing an algorithm that can find an optimal solution. For the two most general problems, we show that any polynomial time algorithm has an arbitrarily bad worst-case performance bound, and propose combined column generation and tabu search heuristic algorithms that can find near optimal solutions for them in a reasonable computational time.

Suggested Citation

  • Feng Li & Zhi-Long Chen & Zhi-Long Chen, 2017. "Integrated Production, Inventory and Delivery Problems: Complexity and Algorithms," INFORMS Journal on Computing, INFORMS, vol. 29(2), pages 232-250, May.
    • Handle: RePEc:inm:orijoc:v:29:y:2017:i:2:p:232-250
    DOI: 10.1287/ijoc.2016.0726
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    Cited by:

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    2. Yunqiang Yin & Doudou Li & Dujuan Wang & T. C. E. Cheng, 2021. "Single-machine serial-batch delivery scheduling with two competing agents and due date assignment," Annals of Operations Research, Springer, vol. 298(1), pages 497-523, March.
    3. Yang, Xianyan & Li, Feng & Liu, Zhixue & Xu, Zhou, 2024. "New exact and heuristic algorithms for general production and delivery integration," European Journal of Operational Research, Elsevier, vol. 316(2), pages 419-442.
    4. Han, Dongya & Yang, Yongjian & Wang, Dujuan & Cheng, T.C.E. & Yin, Yunqiang, 2019. "Integrated production, inventory, and outbound distribution operations with fixed departure times in a three-stage supply chain," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 125(C), pages 334-347.
    5. Feng Li & Zhou Xu & Zhi-Long Chen, 2020. "Production and Transportation Integration for Commit-to-Delivery Mode with General Shipping Costs," INFORMS Journal on Computing, INFORMS, vol. 32(4), pages 1012-1029, October.
    6. Byung-Cheon Choi & Myoung-Ju Park, 2021. "Single-machine scheduling with periodic due dates to minimize the total earliness and tardy penalty," Journal of Combinatorial Optimization, Springer, vol. 41(4), pages 781-793, May.
    7. Li, Feng & Xu, Shifu & Xu, Zhou, 2023. "New exact and approximation algorithms for integrated production and transportation scheduling with committed delivery due dates and order acceptance," European Journal of Operational Research, Elsevier, vol. 306(1), pages 127-140.
    8. Shuo Zhang & Jianyou Xu & Yingli Qiao, 2023. "Multi-Objective Q-Learning-Based Brain Storm Optimization for Integrated Distributed Flow Shop and Distribution Scheduling Problems," Mathematics, MDPI, vol. 11(20), pages 1-25, October.
    9. Bachtenkirch, David & Bock, Stefan, 2022. "Finding efficient make-to-order production and batch delivery schedules," European Journal of Operational Research, Elsevier, vol. 297(1), pages 133-152.
    10. Li, Feng & Yang, Dong & Wang, Shuaian & Weng, Jinxian, 2019. "Ship routing and scheduling problem for steel plants cluster alongside the Yangtze River," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 122(C), pages 198-210.
    11. Li, Chung-Lun & Li, Feng, 2020. "Rescheduling production and outbound deliveries when transportation service is disrupted," European Journal of Operational Research, Elsevier, vol. 286(1), pages 138-148.
    12. Yunqiang Yin & Yongjian Yang & Dujuan Wang & T.C.E. Cheng & Chin‐Chia Wu, 2018. "Integrated production, inventory, and batch delivery scheduling with due date assignment and two competing agents," Naval Research Logistics (NRL), John Wiley & Sons, vol. 65(5), pages 393-409, August.

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