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Mathematical programming heuristics for the production routing problem

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  • Russell, Robert A.

Abstract

This paper develops a framework and solution methodology for optimizing the integration of production, inventory, and distribution for supplying retail demand locations from a production facility. Two mathematical programming-based heuristics are developed which use a relaxed mixed integer model to determine an initial solution. One approach uses set partitioning and another approach employs the concept of seed routes to determine an approximate solution and a vehicle routing metaheuristic is used to sequence routes for each time period in the planning horizon. A multi-iteration improvement procedure determines the final solution. The proposed multi-phase approach achieves many new best known solutions to test problems for this challenging supply chain optimization problem. Additionally, experiments are conducted to assess the inclusion of fixed vehicle costs and the impact on fleet size and solution quality.

Suggested Citation

  • Russell, Robert A., 2017. "Mathematical programming heuristics for the production routing problem," International Journal of Production Economics, Elsevier, vol. 193(C), pages 40-49.
    • Handle: RePEc:eee:proeco:v:193:y:2017:i:c:p:40-49
    DOI: 10.1016/j.ijpe.2017.06.033
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    References listed on IDEAS

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    5. Yossiri Adulyasak & Jean-François Cordeau & Raf Jans, 2014. "Formulations and Branch-and-Cut Algorithms for Multivehicle Production and Inventory Routing Problems," INFORMS Journal on Computing, INFORMS, vol. 26(1), pages 103-120, February.
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    Cited by:

    1. Agostinho Agra & Marielle Christiansen & Lars Magnus Hvattum & Filipe Rodrigues, 2018. "Robust Optimization for a Maritime Inventory Routing Problem," Transportation Science, INFORMS, vol. 52(3), pages 509-525, June.
    2. Li, Yantong & Chu, Feng & Côté, Jean-François & Coelho, Leandro C. & Chu, Chengbin, 2020. "The multi-plant perishable food production routing with packaging consideration," International Journal of Production Economics, Elsevier, vol. 221(C).
    3. Schenekemberg, Cleder M. & Scarpin, Cassius T. & Pécora, José E. & Guimarães, Thiago A. & Coelho, Leandro C., 2021. "The two-echelon production-routing problem," European Journal of Operational Research, Elsevier, vol. 288(2), pages 436-449.
    4. Li, Yantong & Chu, Feng & Chu, Chengbin & Zhu, Zhanguo, 2019. "An efficient three-level heuristic for the large-scaled multi-product production routing problem with outsourcing," European Journal of Operational Research, Elsevier, vol. 272(3), pages 914-927.
    5. Xuanjing Fang & Yanan Du & Yuzhuo Qiu, 2017. "Reducing Carbon Emissions in a Closed-Loop Production Routing Problem with Simultaneous Pickups and Deliveries under Carbon Cap-and-Trade," Sustainability, MDPI, vol. 9(12), pages 1-15, November.
    6. Qiu, Yuzhuo & Zhou, Dan & Du, Yanan & Liu, Jie & Pardalos, Panos M. & Qiao, Jun, 2021. "The two-echelon production routing problem with cross-docking satellites," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 147(C).
    7. Zakaria Chekoubi & Wajdi Trabelsi & Nathalie Sauer & Ilias Majdouline, 2022. "The Integrated Production-Inventory-Routing Problem with Reverse Logistics and Remanufacturing: A Two-Phase Decomposition Heuristic," Sustainability, MDPI, vol. 14(20), pages 1-30, October.
    8. Zu-Jun Ma & Fei Yang & Ying Dai & Zuo-Jun Max Shen, 2021. "The Migratory Beekeeping Routing Problem: Model and an Exact Algorithm," INFORMS Journal on Computing, INFORMS, vol. 33(1), pages 319-335, January.
    9. Manousakis, Eleftherios G. & Kasapidis, Grigoris A. & Kiranoudis, Chris T. & Zachariadis, Emmanouil E., 2022. "An infeasible space exploring matheuristic for the Production Routing Problem," European Journal of Operational Research, Elsevier, vol. 298(2), pages 478-495.
    10. Qiu, Yuzhuo & Ni, Ming & Wang, Liang & Li, Qinqin & Fang, Xuanjing & Pardalos, Panos M., 2018. "Production routing problems with reverse logistics and remanufacturing," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 111(C), pages 87-100.
    11. Abdalrahman Algendi & Sebastián Urrutia & Lars Magnus Hvattum, 2023. "Optimizing production levels in maritime inventory routing with load-dependent speed optimization," Flexible Services and Manufacturing Journal, Springer, vol. 35(1), pages 111-141, March.
    12. Qin, Wei & Sun, Yan-Ning & Zhuang, Zi-Long & Lu, Zhi-Yao & Zhou, Yao-Ming, 2021. "Multi-agent reinforcement learning-based dynamic task assignment for vehicles in urban transportation system," International Journal of Production Economics, Elsevier, vol. 240(C).
    13. Avci, Mustafa & Yildiz, Seyda Topaloglu, 2019. "A matheuristic solution approach for the production routing problem with visit spacing policy," European Journal of Operational Research, Elsevier, vol. 279(2), pages 572-588.

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