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Barry O'Sullivan

Researcher at University College Cork

Publications -  324
Citations -  3966

Barry O'Sullivan is an academic researcher from University College Cork. The author has contributed to research in topics: Constraint programming & Constraint satisfaction problem. The author has an hindex of 29, co-authored 312 publications receiving 3610 citations. Previous affiliations of Barry O'Sullivan include Brown University & National University of Ireland.

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Journal ArticleDOI

Extrapolating from Limited Uncertain Information in Large-Scale Combinatorial Optimization Problems to Obtain Robust Solutions

TL;DR: This paper presents a strategy for extrapolating data from limited uncertain information to ensure a certain level of robustness in the solutions obtained and is motivated and evaluated with real-world applications of harvesting and supplying timber from forests to mills and the well known knapsack problem with uncertainty.
Journal ArticleDOI

Introduction to the Special Issue on Principles and Practice of Constraint Programming (CP 2005)

TL;DR: This special issue, arising from CP 2005, is dedicated to Eugene C. Freuder, whose career has been an inspiration to many constraints researchers.
Proceedings ArticleDOI

Optimal stopping methods for finding high quality solutions to satisfiability problems with preferences

TL;DR: The experimental evaluation shows that the average success rate of the proposed algorithm is a good approximation of the theoretical one of the 1/e-rule, since it is about 50.92% on 1956 structured problems and 48.33% on 2400 randomly generated instances with 200 variables.
Book ChapterDOI

Find Your Way Back: Mobility Profile Mining with Constraints

TL;DR: A constraint model is presented that takes the symmetry of non-noise trajectories into account to produce better clusters in mobility profile mining and shows the efficacy of the approach on real-world data that was previously processed using standard data mining techniques.
Journal ArticleDOI

Erratum to Reformulating table constraints using functional dependencies--an application to explanation generation

TL;DR: It is shown that reformulations can be found that yield compact explanations of inconsistency by reducing both the number of variables required to explain inconsistency and the arity of the largest constraint involved in the explanation.