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

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Principles and Practice of Constraint Programming – CP 2011 (CP 2011)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 6876))

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.

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Author information

Authors and Affiliations

  1. National ICT Australia (NICTA) Ltd., Australia

    M. A. Hakim Newton, Duc Nghia Pham, Abdul Sattar & Michael Maher

  2. Institute for Integrated and Intelligent Systems, Griffith University, Australia

    M. A. Hakim Newton, Duc Nghia Pham & Abdul Sattar

  3. School of Computer Science and Engineering, University of New South Wales, Australia

    Michael Maher

  4. Reasoning Research Institute, Sydney, Australia

    Michael Maher

Authors
  1. M. A. Hakim Newton
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  2. Duc Nghia Pham
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  3. Abdul Sattar
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  4. Michael Maher
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong, China

    Jimmy Lee

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© 2011 Springer-Verlag Berlin Heidelberg

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Newton, M.A.H., Pham, D.N., Sattar, A., Maher, M. (2011). Kangaroo: An Efficient Constraint-Based Local Search System Using Lazy Propagation. In: Lee, J. (eds) Principles and Practice of Constraint Programming – CP 2011. CP 2011. Lecture Notes in Computer Science, vol 6876. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23786-7_49

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  • DOI: https://doi.org/10.1007/978-3-642-23786-7_49

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23785-0

  • Online ISBN: 978-3-642-23786-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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