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(Incremental) priority algorithms
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Source Symposium on Discrete Algorithms archive
Proceedings of the thirteenth annual ACM-SIAM symposium on Discrete algorithms table of contents
San Francisco, California
Pages: 752 - 761  
Year of Publication: 2002
ISBN:0-89871-513-X
Authors
Allan Borodin  University of Toronto
Morten N. Nielsen  University of Southern Denmark, Odense
Charles Rackoff  University of Toronto
Sponsor
SIGACT: ACM Special Interest Group on Algorithms and Computation Theory
Publisher
Society for Industrial and Applied Mathematics  Philadelphia, PA, USA
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Downloads (6 Weeks): 5,   Downloads (12 Months): 34,   Citation Count: 5
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ABSTRACT

We study the question of what optimization problems can be optimally or approximately solved by "greedy-like" algorithms. For definiteness, we will limit the present discussion to some well-studied scheduling problems although the underlying issues apply in a much more general setting. Of course, the main benefit of greedy algorithms lies in both their conceptual simplicity and their computational efficiency. Based on the experience from online competitive analysis, it seems plausible that we should be able to derive approximation bounds for "greedy-like" algorithms exploiting only the conceptual simplicity of these algorithms. To this end, we will provide a precise definition of what we mean by greedy and greedy-like. A full version of this paper is available at http://www.cs.toronto.edu/~ bor/priority.ps.


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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Steve Sieden, Jiri Sgall, and Gerhard Woeginger. Semi-online scheduling with decreasing job sizes. Operations Research Letters, 27(5):215-221, 2000.

Collaborative Colleagues:
Allan Borodin: colleagues
Morten N. Nielsen: colleagues
Charles Rackoff: colleagues