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Incorporating supplier selection and order allocation into the vehicle routing and multi-cross-dock scheduling problem

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  • Mohammad Mahdi Nasiri
  • Ali Rahbari
  • Frank Werner
  • Roya Karimi

Abstract

In the vehicle routing problem with cross-docking (VRPCD), it is assumed that the selected suppliers and the quantity of the products purchased from each supplier are known. This paper presents an MILP model which incorporates supplier selection and order allocation into the VRPCD in a multi-cross-dock system minimising the total costs, including purchasing, transportation, cross-docking, inventory and early/tardy delivery penalty costs. The sensitivity of the model on the key parameters of the objective function is analysed and the supply decisions are evaluated when the coefficients of the distribution cost are changed. A two-stage solution algorithm (TSSA) is proposed and the results of the TSSA for small-sized instances are compared with the exact solutions. Finally, a large-sized real case of an urban freight transport is solved using the TSSA.

Suggested Citation

  • Mohammad Mahdi Nasiri & Ali Rahbari & Frank Werner & Roya Karimi, 2018. "Incorporating supplier selection and order allocation into the vehicle routing and multi-cross-dock scheduling problem," International Journal of Production Research, Taylor & Francis Journals, vol. 56(19), pages 6527-6552, October.
    • Handle: RePEc:taf:tprsxx:v:56:y:2018:i:19:p:6527-6552
    DOI: 10.1080/00207543.2018.1471241
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    Cited by:

    1. Mohammad Amin Amani & Mohammad Mahdi Nasiri, 2023. "A novel cross docking system for distributing the perishable products considering preemption: a machine learning approach," Journal of Combinatorial Optimization, Springer, vol. 45(5), pages 1-32, July.
    2. Islam, Samiul & Amin, Saman Hassanzadeh & Wardley, Leslie J., 2021. "Machine learning and optimization models for supplier selection and order allocation planning," International Journal of Production Economics, Elsevier, vol. 242(C).
    3. Shih-Che Lo, 2022. "A Particle Swarm Optimization Approach to Solve the Vehicle Routing Problem with Cross-Docking and Carbon Emissions Reduction in Logistics Management," Logistics, MDPI, vol. 6(3), pages 1-15, September.
    4. Changbing Jiang & Jiaming Xu & Shufang Li & Xiang Zhang & Yao Wu, 2022. "The Order Allocation Problem and the Algorithm of Network Freight Platform under the Constraint of Carbon Tax Policy," IJERPH, MDPI, vol. 19(17), pages 1-27, September.
    5. Ieva Meidute-Kavaliauskiene & Nihal Sütütemiz & Figen Yıldırım & Shahryar Ghorbani & Renata Činčikaitė, 2022. "Optimizing Multi Cross-Docking Systems with a Multi-Objective Green Location Routing Problem Considering Carbon Emission and Energy Consumption," Energies, MDPI, vol. 15(4), pages 1-24, February.
    6. Fatemeh Faghih-Mohammadi & Mohammad Mahdi Nasiri & Dinçer Konur, 2023. "Cross-dock facility for disaster relief operations," Annals of Operations Research, Springer, vol. 322(1), pages 497-538, March.

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