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A polynomial case of unconstrained zero-one quadratic optimization

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Abstract.

Unconstrained zero-one quadratic maximization problems can be solved in polynomial time when the symmetric matrix describing the objective function is positive semidefinite of fixed rank with known spectral decomposition.

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Authors and Affiliations

  1. Department of Mathematics, EPFL, 1015-Lausanne, Switzerland¶e-mails: {Kim.Allemand, Komei.Fukuda, Thomas.Liebling, Erich.Steiner}@epfl.ch, , , , , , CH

    Kim Allemand, Komei Fukuda, Thomas M. Liebling & Erich Steiner

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  1. Kim Allemand
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  2. Komei Fukuda
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  3. Thomas M. Liebling
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  4. Erich Steiner
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Received: August 2000 / Accepted: March 2001¶Published online May 18, 2001

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Allemand, K., Fukuda, K., Liebling, T. et al. A polynomial case of unconstrained zero-one quadratic optimization. Math. Program. 91, 49–52 (2001). https://doi.org/10.1007/s101070100233

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  • DOI: https://doi.org/10.1007/s101070100233

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