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An LPCC Approach to Nonconvex Quadratic Programs

Jing Hu(huj***at***rpi.edu)
John E. Mitchell(mitchj***at***rpi.edu)
Jong-Shi Pang(jspang***at***uiuc.edu)

Abstract: Filling a gap in nonconvex quadratic programming, this paper shows that the global resolution of a feasible quadratic program (QP), which is not known a priori to be bounded or unbounded below, can be accomplished in finite time by solving a linear program with linear complementarity constraints, i.e., an LPCC. Alternatively, this task can be divided into two LPCCs: the first one confirms whether or not the QP is bounded below on the feasible set and computes a feasible ray on which the QP is unbounded if such a ray exists; the second LPCC computes a globally optimal solution if it exists, by identifying a stationary point that yields the best quadratic objective value. In turn, the global resolution of these LPCCs can be accomplished by a parameter-free, mixed integer-programming based, finitely terminating algorithm developed recently by the authors, which can be enhanced in this context by a new kind of valid cuts derived from the second-order conditions of the QP and by exploiting the special structure of the LPCCs. Throughout, our treatment makes no boundedness assumption of the QP; this is a significant departure from much of the existing literature which consistently employs the boundedness of the feasible set as a blanket assumption. The general theory is illustrated by 3 classes of indefinite problems: QPs with simple upper and lower bounds (existence of optimal solutions is guaranteed); same QPs with an additional inequality constraint (extending the case of simple bound constraints); and nonnegatively constrained copositive QPs (no guarantee of the existence of an optimal solution).

Keywords: Quadratic programming, Benders decomposition, linear programs with complementarity constraints, LPECs.

Category 1: Nonlinear Optimization (Quadratic Programming )

Category 2: Complementarity and Variational Inequalities

Citation: Department of Mathematical Sciences, Rensselaer Polytechnic Institute, Troy, NY 12180. May 29. 2008. http://www.rpi.edu/~mitchj/papers/QP_unbdd.html

Download: [PDF]

Entry Submitted: 05/29/2008
Entry Accepted: 05/29/2008
Entry Last Modified: 05/29/2008

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