An approximate solution method based on tabu search for k-minimum spanning tree problems

H. Katagiri, Tomohiro Hayashida, I. Nishizaki, Jun Ishimatsu
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引用次数: 8

Abstract

This paper considers a new tabu search-based approximate solution algorithm for k-minimum spanning tree problems. One of the features of the proposed algorithm is that it efficiently obtains local optimal solutions without applying minimum spanning tree algorithms. Numerical experimental results show that the proposed method provides a good performance especially for dense graphs in terms of solution accuracy over existing algorithms.
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基于禁忌搜索的k-最小生成树问题近似求解方法
本文提出了一种新的基于禁忌搜索的k最小生成树问题近似解算法。该算法的一个特点是无需使用最小生成树算法即可有效地获得局部最优解。数值实验结果表明,与现有算法相比,该方法在求解密集图方面具有较好的性能。
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