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Intelligent Collaborative Freight Distribution to Reduce Greenhouse Gas Emissions: A Review

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Computational Intelligence Methodologies Applied to Sustainable Development Goals

Part of the book series: Studies in Computational Intelligence ((SCI,volume 1036))

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Abstract

Freight distribution suffers from inefficiencies which are responsible for a significant part of greenhouse gas emissions. In addition, they have a negative impact on the performance of companies by reducing profits and increasing costs. Among the measures that can be taken to mitigate these effects are cooperation mechanisms. In this work we review optimization models for horizontal collaborative freight transport that include environmental and economic criteria. Specifically, we consider models for planning delivery routes and for cross-docking.

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Acknowledgements

This work has been partially funded by the Spanish Ministry of Science and Innovation (project PID2019-104410RB-I00).

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Authors and Affiliations

  1. Universidad de La Laguna, San Cristóbal de La Laguna, Spain

    Christopher Expósito-Izquierdo, Belén Melián-Batista, José A. Moreno-Pérez & J. Marcos Moreno-Vega

  2. Kaizten Analytics, San Cristóbal de La Laguna, Spain

    Airam Expósito-Márquez

Authors
  1. Christopher Expósito-Izquierdo
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  2. Airam Expósito-Márquez
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  3. Belén Melián-Batista
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  4. José A. Moreno-Pérez
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  5. J. Marcos Moreno-Vega
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Corresponding author

Correspondence to J. Marcos Moreno-Vega .

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Editors and Affiliations

  1. Department of Computer Science and Artificial Intelligence, University of Granada, Granada, Spain

    José Luis Verdegay

  2. Department of Engineering of Systems, University of La Laguna, San Cristóbal de La Laguna, Spain

    Julio Brito

  3. Department of Computer Science and Artificial Intelligence, University of Granada, Granada, Spain

    Carlos Cruz

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Expósito-Izquierdo, C., Expósito-Márquez, A., Melián-Batista, B., Moreno-Pérez, J.A., Moreno-Vega, J.M. (2022). Intelligent Collaborative Freight Distribution to Reduce Greenhouse Gas Emissions: A Review. In: Verdegay, J.L., Brito, J., Cruz, C. (eds) Computational Intelligence Methodologies Applied to Sustainable Development Goals. Studies in Computational Intelligence, vol 1036. Springer, Cham. https://doi.org/10.1007/978-3-030-97344-5_9

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