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dc.contributor.authorDang, Nguyen
dc.date.accessioned2022-09-02T15:30:04Z
dc.date.available2022-09-02T15:30:04Z
dc.date.issued2022-07-31
dc.identifier.citationDang , N 2022 , A portfolio-based analysis method for competition results . in ModRef 2022 - The 21st workshop on Constraint Modelling and Reformulation . The 21st workshop on Constraint Modelling and Reformulation , Haifa , Israel , 31/07/22 . < https://modref.github.io/papers/ModRef2022_PortfolioBasedAnalysisMethodForCompetitionResults.pdf >en
dc.identifier.citationworkshopen
dc.identifier.otherPURE: 280770219
dc.identifier.otherPURE UUID: e87ca23e-3c8a-4ffb-9a04-8c310ed78447
dc.identifier.otherORCID: /0000-0002-2693-6953/work/117211369
dc.identifier.urihttp://hdl.handle.net/10023/25940
dc.descriptionNguyen Dang: is a Leverhulme Early Career Fellow.en
dc.description.abstractCompetitions such as the MiniZinc Challenges or the SAT competitions have been very useful sources for comparing performance of different solving approaches and for advancing the state-of-the-arts of the fields. Traditional competition setting often focuses on producing a ranking between solvers based on their average performance across a wide range of benchmark problems and instances. While this is a sensible way to assess the relative performance of solvers, such ranking does not necessarily reflect the full potential of a solver, especially when we want to utilise a portfolio of solvers instead of a single one for solving a new problem. In this paper, I will describe a portfolio-based analysis method which can give complementary insights into the performance of participating solvers in a competition. The method is demonstrated on the results of the MiniZinc Challenges and new insights gained from the portfolio viewpoint are presented.
dc.format.extent11
dc.language.isoeng
dc.relation.ispartofModRef 2022 - The 21st workshop on Constraint Modelling and Reformulationen
dc.rightsCopyright © 2022 by the authors. This work has been made available online in accordance with publisher policies or with permission. Permission for further reuse of this content should be sought from the publisher or the rights holder. This is the final published version of the work, which was originally published at https://modref.github.io/papers/ModRef2022_PortfolioBasedAnalysisMethodForCompetitionResults.pdf.en
dc.subjectAlgorithm portfolioen
dc.subjectAlgorithm selectionen
dc.subjectConstraint programmingen
dc.subjectQA75 Electronic computers. Computer scienceen
dc.subjectNSen
dc.subject.lccQA75en
dc.titleA portfolio-based analysis method for competition resultsen
dc.typeConference itemen
dc.contributor.sponsorThe Leverhulme Trusten
dc.description.versionPublisher PDFen
dc.contributor.institutionUniversity of St Andrews. School of Computer Scienceen
dc.contributor.institutionUniversity of St Andrews. Centre for Interdisciplinary Research in Computational Algebraen
dc.identifier.urlhttps://www-users.cs.york.ac.uk/~frisch/ModRef/en
dc.identifier.urlhttps://modref.github.io/papers/ModRef2022_PortfolioBasedAnalysisMethodForCompetitionResults.pdfen
dc.identifier.urlhttps://arxiv.org/abs/2205.15414en
dc.identifier.grantnumberECF-2020-168en


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