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An effective polynomial-time heuristic for the minimum-cardinality IIS set-covering problem

An effective polynomial-time heuristic for the minimum-cardinality IIS set-covering problem The state-of-the-art methods for analyzing infeasible linear programs concentrate on isolating Irreducible Infeasible Sets (IISs) of constraints. However, when there are numerous infeasibilities in the model, it is also useful to identify a minimum-cardinality set of constraints which, if removed from the LP, renders it feasible. This set of constraintscovers the IISs. This paper presents a heuristic algorithm for finding a small-cardinality set of constraints which covers the IISs in an infeasible LP. Empirical tests show that it finds a true minimum-cardinality cover over all of the examples in a test set, though this performance cannot be guaranteed in general. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Annals of Mathematics and Artificial Intelligence Springer Journals

An effective polynomial-time heuristic for the minimum-cardinality IIS set-covering problem

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References (23)

Publisher
Springer Journals
Copyright
Copyright
Subject
Computer Science; Artificial Intelligence; Mathematics, general; Computer Science, general; Complex Systems
ISSN
1012-2443
eISSN
1573-7470
DOI
10.1007/BF02284627
Publisher site
See Article on Publisher Site

Abstract

The state-of-the-art methods for analyzing infeasible linear programs concentrate on isolating Irreducible Infeasible Sets (IISs) of constraints. However, when there are numerous infeasibilities in the model, it is also useful to identify a minimum-cardinality set of constraints which, if removed from the LP, renders it feasible. This set of constraintscovers the IISs. This paper presents a heuristic algorithm for finding a small-cardinality set of constraints which covers the IISs in an infeasible LP. Empirical tests show that it finds a true minimum-cardinality cover over all of the examples in a test set, though this performance cannot be guaranteed in general.

Journal

Annals of Mathematics and Artificial IntelligenceSpringer Journals

Published: Dec 8, 2005

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