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An algorithm for a singly constrained class of quadratic programs subject to upper and lower bounds

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Abstract

This paper gives an O(n) algorithm for a singly constrained convex quadratic program using binary search to solve the Kuhn-Tucker system. Computational results indicate that a randomized version of this algorithm runs in expected linear time and is suitable for practical applications. For the nonconvex case anε-approximate algorithm is proposed which is based on convex and piecewise linear approximations of the objective function.

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Authors and Affiliations

  1. Computer Science Department, The Pennsylvania State University, 16802, University Park, PA, USA

    P. M. Pardalos & N. Kovoor

Authors
  1. P. M. Pardalos
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  2. N. Kovoor
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Pardalos, P.M., Kovoor, N. An algorithm for a singly constrained class of quadratic programs subject to upper and lower bounds. Mathematical Programming 46, 321–328 (1990). https://doi.org/10.1007/BF01585748

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  • DOI: https://doi.org/10.1007/BF01585748

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