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A Cellular Genetic Algorithm for Solving the Vehicle Routing Problem with Time Windows

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Soft Computing in Industrial Applications

Part of the book series: Advances in Intelligent and Soft Computing ((AINSC,volume 75))

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 kind of structured algorithms is well suited for complex problems. In this paper, a cGA for solving the vehicle routing problem with time windows (VRPTW) is proposed. The benchmark of Solomon is selected for testing the proposed cGAs, and compares them with some other heuristics in the literature. The results demonstrate that the proposed cGA has a good potential for solving this kind of problems.

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References

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Author information

Authors and Affiliations

  1. Department of Computer Science, Islamic Azad University, Mashhad Branch, Iran

    Iman Kamkar

  2. Department of Computer Engineering, Iran University of Science and Technology, Tehran, Iran

    Mahdieh Poostchi

  3. Departments of Electrical Engineering and Computer Engineering, Ferdowsi University of Mashhad, Iran

    Mohammad Reza Akbarzadeh Totonchi

Authors
  1. Iman Kamkar
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  2. Mahdieh Poostchi
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  3. Mohammad Reza Akbarzadeh Totonchi
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Editor information

Editors and Affiliations

  1. Helsinki University, Espoo, Finland

    Xiao-Zhi Gao

  2. University of Minho, Giumaraes, Portugal

    António Gaspar-Cunha

  3. Kyushu Inst. of Technology, Fukuoka, Japan

    Mario Köppen

  4. Loughborough University, Loughborough, UK

    Gerald Schaefer

  5. The Chinese University of Hong Kong, Hong Kong

    Jun Wang

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© 2010 Springer-Verlag Berlin Heidelberg

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Kamkar, I., Poostchi, M., Akbarzadeh Totonchi, M.R. (2010). A Cellular Genetic Algorithm for Solving the Vehicle Routing Problem with Time Windows. In: Gao, XZ., Gaspar-Cunha, A., Köppen, M., Schaefer, G., Wang, J. (eds) Soft Computing in Industrial Applications. Advances in Intelligent and Soft Computing, vol 75. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11282-9_28

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  • DOI: https://doi.org/10.1007/978-3-642-11282-9_28

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-11281-2

  • Online ISBN: 978-3-642-11282-9

  • eBook Packages: EngineeringEngineering (R0)

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