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Solving the Vehicle Routing Problem by Using Cellular Genetic Algorithms

  • Conference paper
Evolutionary Computation in Combinatorial Optimization (EvoCOP 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3004))

Abstract

Cellular Genetic Algorithms (cGAs) are a subclass of Genetic Algorithms (GAs) in which the population diversity and exploration are enhanced thanks to the existence of small overlapped neighborhoods. Such a kind of structured algorithms is specially well suited for complex problems. In this paper we propose the utilization of some cGAs with and without including local search techniques for solving the vehicle routing problem (VRP). A study on the behavior of these algorithms has been performed in terms of the quality of the solutions found, execution time, and number of function evaluations (effort). We have selected the benchmark of Christofides, Mingozzi and Toth for testing the proposed cGAs, and compare them with some other heuristics in the literature. Our conclusions are that cGAs with an added local search operator are able of always locating the optimum of the problem at low times and reasonable effort for the tested instances.

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Author information

Authors and Affiliations

  1. Department of Computer Science, University of Málaga,  

    Enrique Alba

  2. Central Computer Services, University of Málaga,  

    Bernabé Dorronsoro

Authors
  1. Enrique Alba
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  2. Bernabé Dorronsoro
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Editor information

Editors and Affiliations

  1. SAP AG, Neurottstr. 16, 69190, Walldorf, Germany

    Jens Gottlieb

  2. Institute of Computer Graphics and Algorithms, Vienna University of Technology, Favoritenstraße 9–11/1861, 1040, Vienna, Austria

    Günther R. Raidl

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© 2004 Springer-Verlag Berlin Heidelberg

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Alba, E., Dorronsoro, B. (2004). Solving the Vehicle Routing Problem by Using Cellular Genetic Algorithms. In: Gottlieb, J., Raidl, G.R. (eds) Evolutionary Computation in Combinatorial Optimization. EvoCOP 2004. Lecture Notes in Computer Science, vol 3004. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24652-7_2

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  • DOI: https://doi.org/10.1007/978-3-540-24652-7_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-21367-3

  • Online ISBN: 978-3-540-24652-7

  • eBook Packages: Springer Book Archive

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