Bounds on The Performance of a Greedy Algorithm for Probabilities

A bound on the performance of the greedy algorithm for finding the maximum of a submodular set function subject to a cardinality constraint is shown to apply to the problem of selecting a fixed number of events so that the probability that at least one of the selected events occurs is maximized. The...

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Bibliographic Details
Published inMathematics of operations research Vol. 26; no. 2; pp. 313 - 323
Main Authors Gittins, J. C, Harper, G
Format Journal Article
LanguageEnglish
Published Linthicum INFORMS 01.05.2001
Institute for Operations Research and the Management Sciences
Subjects
Algorithms
Drug discovery
Greedy algorithm
Greedy algorithms
Mathematical functions
Mathematical models
Mathematical programming
Mathematical theorems
Objective functions
Pharmaceutical preparations
Preclinical drug evaluation
Probabilities
Studies
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Summary:A bound on the performance of the greedy algorithm for finding the maximum of a submodular set function subject to a cardinality constraint is shown to apply to the problem of selecting a fixed number of events so that the probability that at least one of the selected events occurs is maximized. The bound is improved under an additional assumption which is plausible when the aim is to find a biologically active compound in pharmaceutical research.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
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ISSN:0364-765X
1526-5471
DOI:10.1287/moor.26.2.313.10550