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Multi-neighborhood based iterated tabu search for routing and wavelength assignment problem

Author

Listed:
  • Xinyun Wu

    (Huazhong University of Science and Technology)

  • Shengfeng Yan

    (Huazhong University of Science and Technology)

  • Xin Wan

    (Huazhong University of Science and Technology)

  • Zhipeng Lü

    (Huazhong University of Science and Technology)

Abstract

The routing and wavelength assignment problem (RWA) has shown to be NP-hard if the wavelength continuity constraint and the objective of minimizing the number of wavelengths are considered. This paper introduces a multi-neighborhood based iterated tabu search algorithm (MN-ITS), which consists of three neighborhoods with a unified incremental evaluation method, to solve the min-RWA problem. The proposed MN-ITS algorithm is tested on a set of widely studied real world instances as well as a set of challenging random ones in the literature. Comparison with other reference algorithms shows that the MN-ITS algorithm is able to improve five best upper bounds obtained by other competitive reference algorithms in the literature. This paper also presents an analysis to show the significance of the unified incremental evaluation technique and the combination of multiple neighborhoods.

Suggested Citation

  • Xinyun Wu & Shengfeng Yan & Xin Wan & Zhipeng Lü, 2016. "Multi-neighborhood based iterated tabu search for routing and wavelength assignment problem," Journal of Combinatorial Optimization, Springer, vol. 32(2), pages 445-468, August.
    • Handle: RePEc:spr:jcomop:v:32:y:2016:i:2:d:10.1007_s10878-015-9962-y
    DOI: 10.1007/s10878-015-9962-y
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    References listed on IDEAS

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