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International Conference on Integration of Constraint Programming, Artificial Intelligence, and Operations Research

CPAIOR 2015: Integration of AI and OR Techniques in Constraint Programming pp 231–239Cite as

Combining Constraint Propagation and Discrete Ellipsoid-Based Search to Solve the Exact Quadratic Knapsack Problem

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9075))

Abstract

We propose an extension to the discrete ellipsoid-based search (DEBS) to solve the exact quadratic knapsack problem (EQKP), an important class of optimization problem with a number of practical applications. For the first time, our extension enables DEBS to solve convex quadratically constrained problems with linear constraints. We show that adding linear constraint propagation to DEBS results in an algorithm that is able to outperform both the state-of-the-art MIP solver CPLEX and a semi-definite programming approach by about one order of magnitude on two variations of the EQKP.

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Author information

Authors and Affiliations

  1. Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, Ontario, M5S 3G8, Canada

    Wen-Yang Ku & J. Christopher Beck

Authors
  1. Wen-Yang Ku
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  2. J. Christopher Beck
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Corresponding author

Correspondence to Wen-Yang Ku .

Editor information

Editors and Affiliations

  1. University of Connecticut, Storrs, Connecticut, USA

    Laurent Michel

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© 2015 Springer International Publishing Switzerland

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Ku, WY., Beck, J.C. (2015). Combining Constraint Propagation and Discrete Ellipsoid-Based Search to Solve the Exact Quadratic Knapsack Problem. In: Michel, L. (eds) Integration of AI and OR Techniques in Constraint Programming. CPAIOR 2015. Lecture Notes in Computer Science(), vol 9075. Springer, Cham. https://doi.org/10.1007/978-3-319-18008-3_16

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  • DOI: https://doi.org/10.1007/978-3-319-18008-3_16

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-18007-6

  • Online ISBN: 978-3-319-18008-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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