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Less-than-Truckload Shipper Collaboration in the Physical Internet

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Intelligent Systems and Applications (IntelliSys 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1038))

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Abstract

This paper studies the shippers’ less-than-truckload collaboration in the Physical Internet (PI) for logistics. PI offers a new way to address the efficiency challenges in logistics consolidation through exploiting Internet of Things. The PI facilitates the consolidation of loads from various parties in a much quicker and more efficient way. With the PI, shippers can collaboratively consolidate their freight into truckloads or much larger less-than-truckload loads. Their transportation cost are significantly reduced, due to economies of scale. The collaborative planning problem in the PI is formulated as a non-convex integer network flow model. The problem is generally NP-hard, and a local search heuristic combined with simulate annealing method is developed. The algorithm is evaluated through varied computational examples. This is the first study that investigates shipper collaboration in the PI.

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Acknowledgments

This research is partially supported by Natural Science Foundation of China (Nos. 71531003, 71501039, 71432004), the Leading Talent Program of Guangdong Province (No. 2016LJ06D703), the Shenzhen Science and Technology Innovation Committee (Grant No. ZDSYS20170725140921348), and the Fundamental Research Funds of Southeast University(No. 3214008411).

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Authors and Affiliations

  1. School of Economics and Management, Southeast University, Nanjing, People’s Republic of China

    Minghui Lai

  2. Shenzhen Key Laboratory of IoT Intelligent Systems and Wireless Network Technology, The Shenzhen Research Institute of Big Data, The Chinese University of Hong Kong, Shenzhen, People’s Republic of China

    Xiaoqiang Cai

Authors
  1. Minghui Lai
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  2. Xiaoqiang Cai
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Corresponding author

Correspondence to Xiaoqiang Cai .

Editor information

Editors and Affiliations

  1. School of Computing, Computer Science Research Institute, Ulster University, Newtownabbey, UK

    Yaxin Bi

  2. The Science and Information (SAI) Organization, Bradford, West Yorkshire, UK

    Rahul Bhatia

  3. The Science and Information (SAI) Organization, Bradford, West Yorkshire, UK

    Supriya Kapoor

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Lai, M., Cai, X. (2020). Less-than-Truckload Shipper Collaboration in the Physical Internet. In: Bi, Y., Bhatia, R., Kapoor, S. (eds) Intelligent Systems and Applications. IntelliSys 2019. Advances in Intelligent Systems and Computing, vol 1038. Springer, Cham. https://doi.org/10.1007/978-3-030-29513-4_10

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