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Some Strongly Polynomially Solvable Convex Quadratic Programs with Bounded Variables

Jong-Shi Pang (jongship***at***usc.edu)
Shaoning Han (shaoning***at***usc.edu)

Abstract: This paper begins with a class of convex quadratic programs (QPs) with bounded variables solvable by the parametric principal pivoting algorithm with $\mbox{O}(n^3)$ strongly polynomial complexity, where $n$ is the number of variables of the problem. Extension of the Hessian class is also discussed. Our research is motivated by a preprint [7] wherein the efficient solution of a quadratic program with a tridiagonal Hessian matrix in the quadratic objective is needed for the construction of a polynomial-time algorithm for solving an associated sparse variable selection problem. With the tridiagonal structure, the complexity of the QP algorithm reduces to $\mbox{O}(n^2)$. Our strongly polynomiality results extend previous works of some strongly polynomially solvable linear complementarity problems with a P-matrix [9]; special cases of the extended results include weakly quasi-diagonally dominant problems in addition to the tridiagonal ones.

Keywords: Quadratic programs, strong polynomiality, diagonal dominance, Z-matrix

Category 1: Applications -- OR and Management Sciences

Category 2: Nonlinear Optimization (Quadratic Programming )

Category 3: Nonlinear Optimization

Citation:

Download: [PDF]

Entry Submitted: 12/07/2021
Entry Accepted: 12/07/2021
Entry Last Modified: 12/07/2021

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