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Handbook on Semidefinite, Conic and Polynomial Optimization pp 635–668Cite as

Semidefinite Programming and Constraint Programming

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Part of the book series: International Series in Operations Research & Management Science ((ISOR,volume 166))

Abstract

Recently, semidefinite programming relaxations have been applied in constraint programming to take advantage of the high-quality bounds and precise heuristic guidance during the search for a solution. The purpose of this chapter is to present an overview of these developments, and to provide future research prospects.

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Notes

  1. 1.

    In the literature, domain consistency is also referred to as hyper-arc consistency or generalized arc consistency for historic reasons.

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Acknowledgements

I would like to thank Stefano Gualandi for helpful comments on an earlier draft of the chapter.

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  1. Tepper School of Business, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA, USA

    Willem-Jan van Hoeve

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  1. Department of Mathematics and Industrial, Ecole Polytechnique Montreal, Édouard-Montpetit Boulevard 2350, Montreal, QC, Canada, H3C 3A7

    Miguel F. Anjos

  2. LAAS-CNRS, Avenue du Colonel Roche 7, 31077, Toulouse Cedex 4, France

    Jean B. Lasserre

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van Hoeve, WJ. (2012). Semidefinite Programming and Constraint Programming. In: Anjos, M.F., Lasserre, J.B. (eds) Handbook on Semidefinite, Conic and Polynomial Optimization. International Series in Operations Research & Management Science, vol 166. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-0769-0_22

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