Article

Mathematical Programming

, Volume 46, Issue 1, pp 321-328

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

  • P. M. PardalosAffiliated withComputer Science Department, The Pennsylvania State University
  • , N. KovoorAffiliated withComputer Science Department, The Pennsylvania State University

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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.

Key words

Global optimization separable programming quadratic programming