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A logistics cost function with explicit transport costs

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  • Minken, Harald
  • Johansen, Bjørn Gjerde

Abstract

With a view to construct a new framework to assess the benefits of freight transport improvements, an Economic Order Quantity model with uncertain lead time demand is equipped with detailed transport costs. The problem is to minimise total logistics cost by choosing shipment size, vehicle size and reorder point subject to constraints on vehicle size and annual transport capacity. An analytical solution in all variables except the reorder point is derived, reducing the cost minimisation problem to a well-behaved problem in one dimension only.

Suggested Citation

  • Minken, Harald & Johansen, Bjørn Gjerde, 2019. "A logistics cost function with explicit transport costs," Economics of Transportation, Elsevier, vol. 19(C), pages 1-1.
    • Handle: RePEc:eee:ecotra:v:19:y:2019:i:c:6
    DOI: 10.1016/j.ecotra.2019.04.001
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    References listed on IDEAS

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    1. B R Cobb, 2013. "Mixture distributions for modelling demand during lead time," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 64(2), pages 217-228, February.
    2. John E. Tyworth & Liam O'Neill, 1997. "Robustness of the normal approximation of lead‐time demand in a distribution setting," Naval Research Logistics (NRL), John Wiley & Sons, vol. 44(2), pages 165-186, March.
    3. Vernimmen, Bert & Dullaert, Wout & Willemé, Peter & Witlox, Frank, 2008. "Using the inventory-theoretic framework to determine cost-minimizing supply strategies in a stochastic setting," International Journal of Production Economics, Elsevier, vol. 115(1), pages 248-259, September.
    4. Cobb, Barry R. & Johnson, Alan W. & Rumí, Rafael & Salmerón, Antonio, 2015. "Accurate lead time demand modeling and optimal inventory policies in continuous review systems," International Journal of Production Economics, Elsevier, vol. 163(C), pages 124-136.
    5. W. J. Baumol & H. D. Vinod, 1970. "An Inventory Theoretic Model of Freight Transport Demand," Management Science, INFORMS, vol. 16(7), pages 413-421, March.
    6. Tyworth, John E., 2018. "A note on lead-time paradoxes and a tale of competing prescriptions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 109(C), pages 139-150.
    7. Bert Vernimmen & Frank Witlox, 2003. "The inventory-theoretic approach to modal choice in freight transport: literature review and case study," Brussels Economic Review, ULB -- Universite Libre de Bruxelles, vol. 46(2), pages 5-30.
    8. Tyworth, John E. & Zeng, Amy Zhaohui, 1998. "Estimating the effects of carrier transit-time performance on logistics cost and service," Transportation Research Part A: Policy and Practice, Elsevier, vol. 32(2), pages 89-97, February.
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    Cited by:

    1. Daisik Nam & Minyoung Park, 2020. "Improving the Operational Efficiency of Parcel Delivery Network with a Bi-Level Decision Making Model," Sustainability, MDPI, vol. 12(19), pages 1-19, September.
    2. Lijun Liu & Zhixin Long & Chuangchuang Kou & Haozeng Guo & Xinyu Li, 2023. "Evaluation of the Environmental Cost of Integrated Inbound Logistics: A Case Study of a Gigafactory of a Chinese Logistics Firm," Sustainability, MDPI, vol. 15(15), pages 1-20, July.
    3. Guo, Liquan & Jiang, Changmin & Hou, Weilu & Ng, Adolf K.Y. & Shi, Qin, 2024. "International multimodal transport connectivity assessment of multimodal transport from mainland China to Europe," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 186(C).
    4. Sugeng Santoso & R. Nurhidayat & Gustofan Mahmud & Abdul Mujib Arijuddin, 2021. "Measuring the Total Logistics Costs at the Macro Level: A Study of Indonesia," Logistics, MDPI, vol. 5(4), pages 1-19, October.

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    More about this item

    Keywords

    Logistics; Transport cost; Non-linear optimization; EOQ; Uncertain lead time demand;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • D61 - Microeconomics - - Welfare Economics - - - Allocative Efficiency; Cost-Benefit Analysis
    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise

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