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An Evolutionary Discrete Firefly Algorithm with Novel Operators for Solving the Vehicle Routing Problem with Time Windows

  • Eneko Osaba
  • Roberto Carballedo
  • Xin-She Yang
  • Fernando Diaz
Chapter
Part of the Studies in Computational Intelligence book series (SCI, volume 637)

Abstract

An evolutionary discrete version of the Firefly Algorithm (EDFA) is presented in this chapter for solving the well-known Vehicle Routing Problem with Time Windows (VRPTW). The contribution of this work is not only the adaptation of the EDFA to the VRPTW, but also with some novel route optimization operators. These operators incorporate the process of minimizing the number of routes for a solution in the search process where node selective extractions and subsequent reinsertion are performed. The new operators analyze all routes of the current solution and thus increase the diversification capacity of the search process (in contrast with the traditional node and arc exchange based operators). With the aim of proving that the proposed EDFA and operators are effective, some different versions of the EDFA are compared. The present work includes the experimentation with all the 56 instances of the well-known VRPTW set. In order to obtain rigorous and fair conclusions, two different statistical tests have been conducted.

Keywords

Firefly Algorithm Discrete Firefly Algorithm Vehicle Routing Problem with Time Windows Traveling Salesman Problem Combinatorial optimization 

Notes

Acknowledgments

This project was supported by the European Unions Horizon 2020 research and innovation programme through the TIMON: Enhanced real time services for optimized multimodal mobility relying on cooperative networks and open data project (636220); as well as by the projects TEC2013-45585-C2-2-R from the Spanish Ministry of Economy and Competitiveness, and PC2013-71A from the Basque Government.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Eneko Osaba
    • 1
  • Roberto Carballedo
    • 1
  • Xin-She Yang
    • 2
  • Fernando Diaz
    • 1
  1. 1.Deusto Institute of Technology (DeustoTech)University of DeustoBilbaoSpain
  2. 2.School of Science and TechnologyMiddlesex UniversityLondonUK

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