Scheduling Search Procedures
We analyze preemptive on-line scheduling against randomized adversaries, with the goal to finish an unknown distinguished target job. Our motivation comes from clinical gene search projects, but the subject leads to general theoretical questions of independent interest, including some natural but un...
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Published in | Journal of scheduling Vol. 7; no. 5; pp. 349 - 364 |
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Main Author | |
Format | Journal Article |
Language | English |
Published |
New York
Springer Nature B.V
01.09.2004
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Subjects | |
Online Access | Get full text |
ISSN | 1094-6136 1099-1425 1099-1425 |
DOI | 10.1023/B:JOSH.0000036859.97424.e5 |
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Abstract | We analyze preemptive on-line scheduling against randomized adversaries, with the goal to finish an unknown distinguished target job. Our motivation comes from clinical gene search projects, but the subject leads to general theoretical questions of independent interest, including some natural but unusual probabilistic models. We study problem versions with known and unknown processing times of jobs and target probabilities, and models where the on-line player gets some randomized extra information about the target. For some versions we get optimal competitive ratios, expressed in terms of given parameters of instances. |
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AbstractList | We analyze preemptive on-line scheduling against randomized adversaries, with the goal to finish an unknown distinguished target job. Our motivation comes from clinical gene search projects, but the subject leads to general theoretical questions of independent interest, including some natural but unusual probabilistic models. We study problem versions with known and unknown processing times of jobs and target probabilities, and models where the on-line player gets some randomized extra information about the target. For some versions we get optimal competitive ratios, expressed in terms of given parameters of instances. |
Author | Damaschke, Peter |
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SubjectTerms | Bayesian models Candidates Chromosomes Comparative analysis Computer science Employment Genes Hypotheses Motivation Mutation on-line algorithms Parameter estimation randomized adversary Scheduling searching |
Title | Scheduling Search Procedures |
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