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

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    Author(s)
    Newton, MAH
    Pham, DN
    Sattar, A
    Maher, M
    Griffith University Author(s)
    Sattar, Abdul
    Year published
    2011
    Metadata
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    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.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.
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    Conference Title
    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume
    6876 LNCS
    Publisher URI
    http://www.dmi.unipg.it/cp2011/papers.html
    DOI
    https://doi.org/10.1007/978-3-642-23786-7_49
    Copyright Statement
    © 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
    Subject
    Artificial intelligence not elsewhere classified
    Publication URI
    http://hdl.handle.net/10072/40879
    Collection
    • Conference outputs

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