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Published in: Journal of Combinatorial Optimization 2/2016

01-08-2016

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

Authors: Xinyun Wu, Shengfeng Yan, Xin Wan, Zhipeng Lü

Published in: Journal of Combinatorial Optimization | Issue 2/2016

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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.

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Footnotes
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Metadata
Title
Multi-neighborhood based iterated tabu search for routing and wavelength assignment problem
Authors
Xinyun Wu
Shengfeng Yan
Xin Wan
Zhipeng Lü
Publication date
01-08-2016
Publisher
Springer US
Published in
Journal of Combinatorial Optimization / Issue 2/2016
Print ISSN: 1382-6905
Electronic ISSN: 1573-2886
DOI
https://doi.org/10.1007/s10878-015-9962-y

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