A taub search algorthm for k-minimum spanning tree problems

Hideki Katagiri; Masatoshi Sakawa; Ichiro Nishizaki; Kosuke Kato; Tomohiro Hayashida

doi:10.14864/softscis.2006.0.1524.0

SCIS & ISIS 2006

Session ID : FR-J4-5

DOI https://doi.org/10.14864/softscis.2006.0.1524.0

Conference information

Host: Japan SOciety for Fuzzy Theory and intelligent informatics

Co-host: The Korea Fuzzy Logic and Intelligent Systems Society, IEEE Computational Intelligence Society, The International Fuzzy Systems Association, 21th Century COE Program "Creation of Agent-Based Social Systems Sciences"

FR-J4 Soft Computing Approaches for Systems Optimization and Analysis

A taub search algorthm for k-minimum spanning tree problems

*Hideki Katagiri, Masatoshi Sakawa, Ichiro Nishizaki, Kosuke Kato, Tomohiro Hayashida

Author information

Keywords: k-minimum spanning tree problem, tabu search, combinatorial optimization

CONFERENCE PROCEEDINGS FREE ACCESS

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Abstract

A k-minimum spanning tree (k-MST) problem is a combinatorial problem to seek the subtree with exactly k edges in a given graph. Since the k-MST problem is an NP-hard problem, it is difficult to solve large-scale problems within a practically feasible time. Therefore, it is important to construct an efficient approximate solution algorithm. Blum et al. constructed several metaheuristic approaches. This paper proposes a new tabu search algorithm for k-MST problems and shows that the proposed approach have an advantage for large k over the existing methods.

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