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 inJournal of scheduling Vol. 7; no. 5; pp. 349 - 364
Main Author Damaschke, Peter
Format Journal Article
LanguageEnglish
Published New York Springer Nature B.V 01.09.2004
Subjects
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ISSN1094-6136
1099-1425
1099-1425
DOI10.1023/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.
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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Cites_doi 10.1007/3-540-45471-3_27
10.1007/3-540-44436-X_3
10.1007/BFb0029570
10.1007/3-540-36494-3_24
10.1137/S0097539796299540
10.1016/0304-3975(94)90151-1
10.1006/inco.1993.1054
10.1007/3-540-44666-4_8
10.1145/380752.380782
10.1007/3-540-45465-9_68
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StartPage 349
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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