Kangaroo: An Efficient Constraint-Based Local Search System using Lazy Propagation

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Title Kangaroo: An Efficient Constraint-Based Local Search System using Lazy Propagation
Author Newton, M.A.Hakim; Pham, Nghia; Sattar, Abdul; Maher, Michael
Publication Title Proceedings of 17th International Conference on Principles and Practice of Constraint Programming (CP2011)
Editor Jimmy Lee
Year Published 2011
Place of publication United Kingdom
Publisher Springer
Abstract In this paper, we introduce Kangaroo, a constraint-based local search system. While existing systems such as Comet maintain invariants after every move, Kangaroo adopts a lazy strategy, updating invariants only when they are needed. Our empirical evaluation shows that Kangaroo consistently has a smaller memory footprint than Comet, and is usually significantly faster.
Peer Reviewed Yes
Published Yes
Publisher URI http://www.dmi.unipg.it/cp2011/papers.html
Alternative URI http://dx.doi.org/10.1007/978-3-642-23786-7_49
Copyright Statement Copyright 2011 Springer Berlin / Heidelberg. This is the author-manuscript version of this paper. Reproduced in accordance with the copyright policy of the publisher. The original publication is available at www.springerlink.com
ISBN 1611-3349
Conference name 17th International Conference on Principles and Practice of Constraint Programming (CP2011)
Location Perugia, Italy
Date From 2011-09-12
Date To 2011-09-16
URI http://hdl.handle.net/10072/40879
Date Accessioned 2011-07-19
Language en_US
Research Centre Institute for Integrated and Intelligent Systems
Faculty Faculty of Science, Environment, Engineering and Technology
Subject Artificial Intelligence and Image Processing
Publication Type Conference Publications (Full Written Paper - Refereed)
Publication Type Code e1

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