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Proceedings of the Thirty-Sixth Annual ACM Symposium on Theory of Computing 2004
DOI: 10.1145/1007352.1007385
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Approximation algorithms for deadline-TSP and vehicle routing with time-windows

Abstract: Given a metric space G on n nodes, with a start node r and deadlines D(v) for each vertex v, we consider the Deadline-TSP problem of finding a path starting at r that visits as many nodes as possible by their deadlines. We also consider the more general Vehicle Routing with TimeWindows problem, in which each node v also has a releasetime R(v) and the goal is to visit as many nodes as possible within their "time-windows" [R(v), D(v)]. No good approximations were known previously for these problems on general me… Show more

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Cited by 179 publications
(209 citation statements)
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References 24 publications
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“…The Collection and Delivery Problem (CDP) is a subproblem of the PDP in which there is only a single delivery point. Approximation algorithms with guarantees have been developed for the VRP with release times at which jobs can first be performed but without deadlines [4], for the VRP with time windows [2], and for the CPDP [6,11].…”
Section: Related Workmentioning
confidence: 99%
“…The Collection and Delivery Problem (CDP) is a subproblem of the PDP in which there is only a single delivery point. Approximation algorithms with guarantees have been developed for the VRP with release times at which jobs can first be performed but without deadlines [4], for the VRP with time windows [2], and for the CPDP [6,11].…”
Section: Related Workmentioning
confidence: 99%
“…The minimization of the path P′ is a NP-Hard problem called the traveling salesman problem with deadlines in metric spaces, Δ-D L TSP, where the path to minimize can not be a cycle. A lot of work has been done to try to solve the Δ-D L TSP problem Bckenhauer et al (2009);Bansal et al (2004). In this paper the nearest neighbor strategy has been used to get P' from P and t, that is, the new task is inserted between each two tasks in the path P, and the shortest one is selected.…”
Section: Multi-task Per Robot: Mt-sr-ia Approachesmentioning
confidence: 99%
“…I/O scheduling has been studied aggressively [2,4,19,22,37] especially since the speed of disk lags far behind the CPU and RAM speeds.…”
Section: I/o Schedulersmentioning
confidence: 99%