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Studying the Impact of Perturbation Methods on the Efficiency of GVNS for the ATSP

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Variable Neighborhood Search (ICVNS 2018)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11328))

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Abstract

In this work we examine the impact of three shaking procedures on the performance of a GVNS metaheuristic algorithm for solving the Asymmetric Travelling Salesman Problem (ATSP). The first shaking procedure is a perturbation method that is commonly used in the literature as intensified shaking method. The second one is a quantum-inspired shaking method, while the third one is a shuffle method. The shaped GVNS schemes are tested with both first and best improvement and with a time limit of one and two minutes. Experimental analysis shows that the first two methods perform equivalently and much better than the shuffle approach, when using the best improvement strategy. The first method also outperforms the other two when using the first improvement strategy, while the second method produces results that are closer to the results of the third in this case.

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Author information

Authors and Affiliations

  1. Department of Informatics, Ionian University, 7 Tsirigoti Square, Corfu, Greece

    Christos Papalitsas & Theodore Andronikos

  2. Department of Applied Informatics, University of Macedonia, Thessaloniki, Greece

    Panagiotis Karakostas

Authors
  1. Christos Papalitsas
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  2. Theodore Andronikos
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  3. Panagiotis Karakostas
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Corresponding author

Correspondence to Christos Papalitsas .

Editor information

Editors and Affiliations

  1. University of Macedonia, Thessaloniki, Greece

    Angelo Sifaleras

  2. University of Kent, Canterbury, UK

    Said Salhi

  3. Royal Military College of Canada, Kingston, ON, Canada

    Jack Brimberg

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Papalitsas, C., Andronikos, T., Karakostas, P. (2019). Studying the Impact of Perturbation Methods on the Efficiency of GVNS for the ATSP. In: Sifaleras, A., Salhi, S., Brimberg, J. (eds) Variable Neighborhood Search. ICVNS 2018. Lecture Notes in Computer Science(), vol 11328. Springer, Cham. https://doi.org/10.1007/978-3-030-15843-9_22

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  • DOI: https://doi.org/10.1007/978-3-030-15843-9_22

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-15842-2

  • Online ISBN: 978-3-030-15843-9

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