Abstract
This paper considers an efficient approximate algorithm for solving k-minimum spanning tree problems which is one of the combinatorial optimization in networks. A new hybrid algorithm based on tabu search and ant colony optimization is provided. Results of numerical experiments show that the proposed method updates some of the best known values and that the proposed method provides a relatively better performance with solution accuracy over existing algorithms.
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Katagiri, H., Hayashida, T., Nishizaki, I., Ishimatsu, J. (2009). A Hybrid Algorithm Based on Tabu Search and Ant Colony Optimization for k-Minimum Spanning Tree Problems. In: Torra, V., Narukawa, Y., Inuiguchi, M. (eds) Modeling Decisions for Artificial Intelligence. MDAI 2009. Lecture Notes in Computer Science(), vol 5861. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04820-3_29
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DOI: https://doi.org/10.1007/978-3-642-04820-3_29
Publisher Name: Springer, Berlin, Heidelberg
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