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 -