TY - JOUR

T1 - Approximation algorithms with bounded performance guarantees for the clustered traveling salesman problem

AU - Guttmann-Beck, N.

AU - Hassin, R.

AU - Khuller, S.

AU - Raghavachari, B.

PY - 2000/12

Y1 - 2000/12

N2 - Let G = (V, E) be a complete undirected graph with vertex set V, edge set E, and edge weights l(e) satisfying triangle inequality. The vertex set V is partitioned into clusters V1,..., Vk. The clustered traveling salesman problem is to compute a shortest Hamiltonian cycle (tour) that visits all the vertices, and in which the vertices of each cluster are visited consecutively. Since this problem is a generalization of the traveling salesman problem, it is NP-hard. In this paper we consider several variants of this basic problem and provide polynomial time approximation algorithms for them.

AB - Let G = (V, E) be a complete undirected graph with vertex set V, edge set E, and edge weights l(e) satisfying triangle inequality. The vertex set V is partitioned into clusters V1,..., Vk. The clustered traveling salesman problem is to compute a shortest Hamiltonian cycle (tour) that visits all the vertices, and in which the vertices of each cluster are visited consecutively. Since this problem is a generalization of the traveling salesman problem, it is NP-hard. In this paper we consider several variants of this basic problem and provide polynomial time approximation algorithms for them.

KW - Approximation algorithms

KW - Clustered traveling salesman

KW - Traveling salesman problem

UR - http://www.scopus.com/inward/record.url?scp=0011936218&partnerID=8YFLogxK

U2 - 10.1007/s004530010045

DO - 10.1007/s004530010045

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AN - SCOPUS:0011936218

SN - 0178-4617

VL - 28

SP - 422

EP - 437

JO - Algorithmica

JF - Algorithmica

IS - 4

ER -