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Symmetry breaking for exact solutions in adjustable robust optimisation

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Abstract

One of the key unresolved challenges in Adjustable Robust Optimisation is how to deal with large discrete uncertainty sets. In this paper we present a technique for handling such sets based on symmetry breaking ideas from Constraint Programming. In earlier work we applied the technique to a pre-disaster planning problem modelled as a two-stage Stochastic Program, and we were able to solve exactly instances that were previously considered intractable and only had approximate solutions. In this paper we show that the technique can also be applied to an adjustable robust formulation that scales up to larger instances than the stochastic formulation. We also describe a new fast symmetry breaking heuristic that gives improved results.

Original languageEnglish
Title of host publicationECAI 2014 - 21st European Conference on Artificial Intelligence, Including Prestigious Applications of Intelligent Systems, PAIS 2014, Proceedings
EditorsTorsten Schaub, Gerhard Friedrich, Barry O'Sullivan
PublisherIOS Press BV
Pages741-746
Number of pages6
ISBN (Electronic)9781614994183
DOIs
Publication statusPublished - 2014
Event21st European Conference on Artificial Intelligence, ECAI 2014 - Prague, Czech Republic
Duration: 18 Aug 201422 Aug 2014

Publication series

NameFrontiers in Artificial Intelligence and Applications
Volume263
ISSN (Print)0922-6389
ISSN (Electronic)1879-8314

Conference

Conference21st European Conference on Artificial Intelligence, ECAI 2014
Country/TerritoryCzech Republic
CityPrague
Period18/08/1422/08/14

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