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Soft Computing Methods in Transport and Logistics

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Soft Computing Based Optimization and Decision Models

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 360))

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Abstract

The current economic context generates in supply chain management greater demands for flexibility and dynamism. In addition, there is an increase in uncertainty that adds more complexity to the problems associated with planning and management. Soft Computing offers a set of methodologies capable of responding to these challenges. This work provides an overview of transport and logistics problems, as well as the most representative combinatorial optimization models. Specifically, it focuses on the treatment of uncertainty through fuzzy optimization and metaheuristics methodologies. Promising results from the use of this approach suggest emerging areas of application, which are presented and described.

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Acknowledgements

This work has been partially funded by the Spanish Ministry of Economy and Competitiveness with FEDER funds (TIN2015-70226-R) and supported by Fundación Cajacanarias research funds (project 2016TUR19). Contributions from A. Expósito is supported by the ACIISI of the Gobierno de Canarias and FSE.

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  1. Grupo de Computación Inteligente, Instituto Universitario de Desarrollo Regional, Universidad de La Laguna, La Laguna, Spain

    Julio Brito, Dagoberto Castellanos-Nieves, Airam Expósito & José. A. Moreno

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  1. Julio Brito
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  4. José. A. Moreno
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  1. Department of Computer Science and A.I. Higher Technical School of Information Technology and Telecommunications Engineering, University of Granada, Granada, Spain

    David A. Pelta

  2. Department of Computer Science and A.I. Higher Technical School of Information Technology and Telecommunications Engineering, University of Granada , Granada, Spain

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Brito, J., Castellanos-Nieves, D., Expósito, A., Moreno, J.A. (2018). Soft Computing Methods in Transport and Logistics. In: Pelta, D., Cruz Corona, C. (eds) Soft Computing Based Optimization and Decision Models. Studies in Fuzziness and Soft Computing, vol 360. Springer, Cham. https://doi.org/10.1007/978-3-319-64286-4_3

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