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A Decision Support System for Logistics Operations

  • María D. R-Moreno
  • David Camacho
  • David F. Barrero
  • Miguel Gutierrez
Conference paper
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 73)

Abstract

This paper describes an Artificial Intelligence based application for a logistic company that solves the problem of grouping by zones the packages that have to be delivered and propose the routes that the drivers should follow. The tool combines from the one hand, Case-Based Reasoning techniques to separate and learn the most frequent areas or zones that the experienced logistic operators do. These techniques allow the company to separate the daily incidents that generate noise in the routes, from the decision made based on the knowledge of the route. From the other hand, we have used Evolutionary Computation to plan optimal routes from the learning areas and evaluate those routes. The application allows the users to decide under what parameters (i.e. distance, time, etc) the route should be optimized.

Keywords

Genetic Algorithm Geographic Information System Decision Support System Postal Code Evolutionary Computation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • María D. R-Moreno
    • 1
  • David Camacho
    • 2
  • David F. Barrero
    • 1
  • Miguel Gutierrez
    • 3
  1. 1.Departmento de Automática.Universidad de AlcaláMadridSpain
  2. 2.Departamento de Informática.Universidad Autónoma de MadridMadridSpain
  3. 3.Espi & Le Barbier 

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