An improved approximation algorithm for the clustered traveling salesman problem

Authors:
Xiaoguang Bao;Zhaohui Liu
Affiliations:
Department of Mathematics, East China University of Science and Technology, Shanghai 200237, China;Department of Mathematics, East China University of Science and Technology, Shanghai 200237, China
Venue:
Information Processing Letters
Year:
2012

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Abstract

Given a weighted undirected graph G=(V,E), where the vertex set V is partitioned into K clusters V"1,...,V"K, the clustered traveling salesman problem is to compute a shortest tour so that all vertices are visited and the vertices of each cluster are visited consecutively. Supposing that no starting and ending vertices of any cluster are specified, we provide a 13/6(~2.17)-approximation algorithm, and improve the previous approximation ratio of 2.75 due to Guttmann-Beck, Hassin, Khuller, and Raghavachari [Algorithmica 28 (2000) 422-437].