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A Hybrid Cellular Genetic Algorithm for the Capacitated Vehicle Routing Problem

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Book cover Engineering Evolutionary Intelligent Systems

Part of the book series: Studies in Computational Intelligence ((SCI,volume 82))

Summary

Cellular genetic algorithms (cGAs) are a kind of genetic algorithm (GA) — population based heuristic — with a structured population so that each individual can only interact with its neighbors. The existence of small overlapped neighborhoods in this decentralized population provides both diversity and opportunities for exploration, while the exploitation of the search space is strengthened inside each neighborhood. This balance between intensification and diversification makes cGAs naturally suitable for solving complex problems. In this chapter, we solve a large benchmark (composed of 160 instances) of the Capacitated Vehicle Routing Problem (CVRP) with a cGA hybridized with a problem customized recombination operation, an advanced mutation operator integrating three mutation methods, and two well-known local search algorithms for routing problems. The studied test-suite contains almost every existing instance for CVRP in the literature. In this work, the best-so-far solution is found (or even improved) in 80% of the tested instances (126 out of 160), and in the other cases (20%, i.e. 34 out of 160) the deviation between our best solution and the best-known one is always very low (under 2.90%). Moreover, 9 new best-known solutions have been found.

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Author information

Authors and Affiliations

  1. Department of Computer Science, University of Málaga, Spain

    Enrique Alba & Bernabé Dorronsoro

Authors
  1. Enrique Alba
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  2. Bernabé Dorronsoro
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Editor information

Editors and Affiliations

  1. Centre for Quantifiable Quality of Service in Communication Systems (Q2S), Centre of Excellence Norwegian University of Science and Technology, O.S. Bragstads plass 2E, N-7491, Trondheim, Norway

    Ajith Abraham

  2. Department of Computer Science Faculty of Mathematics and Computer Science, Babes-Bolyai University, Cluj-Napoca, Kogalniceanu 1, 400084, Cluj - Napoca, Romania

    Crina Grosan

  3. Department of Electrical & Computer Engineering, University of Alberta, ECERF Bldg., 2nd floor, Edmonton, AB, T6G 2V4, Canada

    Witold Pedrycz

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© 2008 Springer-Verlag Berlin Heidelberg

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Alba, E., Dorronsoro, B. (2008). A Hybrid Cellular Genetic Algorithm for the Capacitated Vehicle Routing Problem. In: Abraham, A., Grosan, C., Pedrycz, W. (eds) Engineering Evolutionary Intelligent Systems. Studies in Computational Intelligence, vol 82. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75396-4_14

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  • DOI: https://doi.org/10.1007/978-3-540-75396-4_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-75395-7

  • Online ISBN: 978-3-540-75396-4

  • eBook Packages: EngineeringEngineering (R0)

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