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Computational study of a family of mixed-integer quadratic programming problems

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Abstract

We present computational experience with a branch-and-cut algorithm to solve quadratic programming problems where there is an upper bound on the number of positive variables. Such problems arise in financial applications. The algorithm solves the largest real-life problems in a few minutes of run-time.

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Authors and Affiliations

  1. Department of Industrial Engineering and Operations Research, Columbia University, Room 331 Mudd, 10027-6699, New York, NY, USA

    Daniel Bienstock

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  1. Daniel Bienstock
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Bienstock, D. Computational study of a family of mixed-integer quadratic programming problems. Mathematical Programming 74, 121–140 (1996). https://doi.org/10.1007/BF02592208

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  • DOI: https://doi.org/10.1007/BF02592208

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