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A Food Transportation Framework for an Efficient and Worker-Friendly Fresh Food Physical Internet

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  • Amitangshu Pal

    (Computer and Information Sciences, Temple University, Philadelphia, PA 19122, USA
    These authors contributed equally to this work.)

  • Krishna Kant

    (Computer and Information Sciences, Temple University, Philadelphia, PA 19122, USA
    These authors contributed equally to this work.)

Abstract

In this paper, we introduce a physical Internet architecture for fresh food distribution networks with the goal of meeting the key challenges of maximizing the freshness of the delivered product and minimizing waste. The physical Internet (PI) architecture is based on the fundamental assumptions of infrastructure sharing among various parties, standardized addressing of all entities and modularized operations. In this paper, we enhance the PI architecture by including a freshness metric and the space-efficient loading/unloading of heterogeneous perishable goods onto the trucks depending on their delivery requirements. We also discuss mechanisms for reducing empty miles of trucks and the carbon footprint of the logistics while reducing the driver’s away-from-home time for long distance delivery. Via extensive simulations, the paper shows that the proposed architecture reduces the driver’s away-from-home time by ∼93%, whereas it improves the food delivery freshness by ∼5%. We show that there is a clear tradeoff between the transportation efficiency of the trucks and the delivery freshness of the food packages.

Suggested Citation

  • Amitangshu Pal & Krishna Kant, 2017. "A Food Transportation Framework for an Efficient and Worker-Friendly Fresh Food Physical Internet," Logistics, MDPI, vol. 1(2), pages 1-21, December.
    • Handle: RePEc:gam:jlogis:v:1:y:2017:i:2:p:10-:d:121529
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    References listed on IDEAS

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    5. Berbeglia, Gerardo & Cordeau, Jean-François & Laporte, Gilbert, 2010. "Dynamic pickup and delivery problems," European Journal of Operational Research, Elsevier, vol. 202(1), pages 8-15, April.
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