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An efficient mixed integer programming model for pairing containers in inland transportation based on the assignment of orders

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  • Hajem A. Daham

    (University of Essex)

  • Xinan Yang

    (University of Essex)

  • Michaela K. Warnes

    (University of Essex)

Abstract

The inland transportation takes a significant portion of the total cost that arises from intermodal transportation. In addition, there are many parties (shipping lines, haulage companies, customers) who share this operation as well as many restrictions that increase the complexity of this problem and make it NP-hard. Therefore, it is important to create an efficient strategy to manage this process in a way to ensure all parties are satisfied. This paper investigates the pairing of containers/orders in drayage transportation from the perspective of delivering paired containers on 40-ft truck and/or individual containers on 20-ft truck, between a single port and a list of customer locations. An assignment mixed integer linear programming model is formulated, which solves the problem of how to combine orders in delivery to save the total transportation cost when orders with both single and multiple destinations exist. In opposition to the traditional models relying on the vehicle routing problem with simultaneous pickups and deliveries and time windows formulation, this model falls into the assignment problem category which is more efficient to solve on large size instances. Another merit for the proposed model is that it can be implemented on different variants of the container drayage problem: import only, import–inland and import–inland–export. Results show that in all cases the pairing of containers yields less cost compared to the individual delivery and decreases empty tours. The proposed model can be solved to optimality efficiently (within half hour) for over 300 orders.

Suggested Citation

  • Hajem A. Daham & Xinan Yang & Michaela K. Warnes, 2017. "An efficient mixed integer programming model for pairing containers in inland transportation based on the assignment of orders," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(6), pages 678-694, June.
    • Handle: RePEc:pal:jorsoc:v:68:y:2017:i:6:d:10.1057_s41274-016-0132-0
    DOI: 10.1057/s41274-016-0132-0
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    References listed on IDEAS

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    Cited by:

    1. Wenqing He & Zhihong Jin & Ying Huang & Shida Xu, 2021. "The Inland Container Transportation Problem with Separation Mode Considering Carbon Dioxide Emissions," Sustainability, MDPI, vol. 13(3), pages 1-16, February.
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    3. Bustos-Coral, Daniel & Costa, Alysson M., 2022. "Drayage routing with heterogeneous fleet, compatibility constraints, and truck load configurations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 168(C).
    4. Xinan Yang & Hajem A. Daham, 2020. "A column generation-based decomposition and aggregation approach for combining orders in inland transportation of containers," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 42(1), pages 261-296, March.
    5. Escudero-Santana, Alejandro & Muñuzuri, Jesús & Cortés, Pablo & Onieva, Luis, 2021. "The one container drayage problem with soft time windows," Research in Transportation Economics, Elsevier, vol. 90(C).
    6. Junseung Kim & Kyungku Kim & Kum Fai Yuen & Keun-Sik Park, 2020. "Cost and Scenario Analysis of Intermodal Transportation Routes from Korea to the USA: After the Panama Canal Expansion," Sustainability, MDPI, vol. 12(16), pages 1-20, August.
    7. Subrata Mitra & Balram Avittathur, 2018. "Application of linear programming in optimizing the procurement and movement of coal for an Indian coal-fired power-generating company," DECISION: Official Journal of the Indian Institute of Management Calcutta, Springer;Indian Institute of Management Calcutta, vol. 45(3), pages 207-224, September.

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