Exact arborescences, matchings and cycles
Discrete Applied Mathematics
Efficient solutions to some transportation problems with applications to minimizing robot arm travel
SIAM Journal on Computing
Preemptive ensemble motion planning on a tree
SIAM Journal on Computing
Nonpreemptive ensemble motion planning on a tree
Journal of Algorithms
On approximating arbitrary metrices by tree metrics
STOC '98 Proceedings of the thirtieth annual ACM symposium on Theory of computing
Routing a vehicle of capacity greater than one
Discrete Applied Mathematics
A threshold of ln n for approximating set cover
Journal of the ACM (JACM)
Euler is standing in line dial-a-ride problems with precedence-constraints
Discrete Applied Mathematics - special issue on the 25th international workshop on graph theoretic concepts in computer science (WG'99)
Approximating a Finite Metric by a Small Number of Tree Metrics
FOCS '98 Proceedings of the 39th Annual Symposium on Foundations of Computer Science
On the approximability of trade-offs and optimal access of Web sources
FOCS '00 Proceedings of the 41st Annual Symposium on Foundations of Computer Science
Probabilistic approximation of metric spaces and its algorithmic applications
FOCS '96 Proceedings of the 37th Annual Symposium on Foundations of Computer Science
Semi-preemptive routing on a linear and circular track
Discrete Optimization
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We study a variant of the pickup-and-delivery problem (PDP) in which the objects that have to be transported can be reloaded at most d times, for a given d@?N. This problem is known to be polynomially solvable on paths or cycles and NP-complete on trees. We present a (4/3+@e)-approximation algorithm if the underlying graph is a tree. By using a result of Charikar et al. [M. Charikar, C. Chekuri, A. Goel, S. Guha, S. Plotkin, Approximating a finite metric by a small number of tree metrics, in: FOCS '98: Proceedings of the 39th Annual Symposium on Foundations of Computer Science, IEEE Computer Society, Washington, DC, USA, 1998, pp. 379-388], this can be extended to a O(lognloglogn)-approximation for general graphs.