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Approximation algorithms for deadline-TSP and vehicle routing with time-windows
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Annual ACM Symposium on Theory of Computing archive
Proceedings of the thirty-sixth annual ACM symposium on Theory of computing table of contents
Chicago, IL, USA
SESSION: Session 5A table of contents
Pages: 166 - 174  
Year of Publication: 2004
ISBN:1-58113-852-0
Authors
Nikhil Bansal  Carnegie Mellon University, Pittsburgh, PA
Avrim Blum  Carnegie Mellon University, Pittsburgh, PA
Shuchi Chawla  Carnegie Mellon University, Pittsburgh, PA
Adam Meyerson  University of California, Los Angeles, CA
Sponsors
ACM: Association for Computing Machinery
SIGACT: ACM Special Interest Group on Algorithms and Computation Theory
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 15,   Downloads (12 Months): 112,   Citation Count: 7
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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 Time-Windows problem, in which each node v also has a release-time 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 metric spaces. We give an O(logn) approximation algorithm for Deadline-TSP, and extend this algorithm to an O(log2n) approximation for the Time-Window problem. We also give a bicriteria approximation algorithm for both problems: Given an ε>0, our algorithm produces a (1/ε) approximation, while exceeding the deadlines by a factor of 1+ε. We use as a subroutine for these results a constant-factor approximation that we develop for a generalization of the orienteering problem in which both the start and the end nodes of the path are fixed. In the process, we give a 3-approximation to the orienteering problem, improving on the previously best known 4-approximation of [6].


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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CITED BY  7

Collaborative Colleagues:
Nikhil Bansal: colleagues
Avrim Blum: colleagues
Shuchi Chawla: colleagues
Adam Meyerson: colleagues