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A scenario-based approach for robust linear optimization

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Published
Publication date2011
Host publicationTheory and Practice of Algorithms in (Computer) Systems
EditorsAlberto Marchetti-Spaccamela, Michael Segal
Place of PublicationBerlin
PublisherSpringer
Pages139-150
Number of pages12
ISBN (electronic)9783642197543
ISBN (print)9783642197536
<mark>Original language</mark>English
Event1st International ICST Conference on Theory and Practice of Algorithms in (Computer) Systems, TAPAS 2011 - Rome, Italy
Duration: 18/04/201120/04/2011

Conference

Conference1st International ICST Conference on Theory and Practice of Algorithms in (Computer) Systems, TAPAS 2011
Country/TerritoryItaly
CityRome
Period18/04/1120/04/11

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer
Volume6595
ISSN (Print)0302-9743
ISSN (electronic)1611-3349

Conference

Conference1st International ICST Conference on Theory and Practice of Algorithms in (Computer) Systems, TAPAS 2011
Country/TerritoryItaly
CityRome
Period18/04/1120/04/11

Abstract

Finding robust solutions of an optimization problem is an important issue in practice. The established concept of Ben-Tal et al. [2] requires that a robust solution is feasible for all possible scenarios. However, this concept is very conservative and hence may lead to solutions with a bad objective value and is in many cases hard to solve. Thus it is not suitable for most practical applications. In this paper we suggest an algorithm for calculating robust solutions that is easy to implement and not as conservative as the strict robustness approach. We show some theoretical properties of our approach and evaluate it using linear programming problems from NetLib.