Now showing items 1-10 of 54
Linear programming via a quadratic penalty function
(Physica - Verlag, 1996)
We use quadratic penalty functions along with some recent ideas from linear l1 estimation to arrive at a new characterization of primal optimal solutions in linear programs. The algorithmic implications of this analysis ...
Piecewise-linear pathways to the optimal solution set in linear programming
(Kluwer Academic Publishers - Plenum Publishers, 1997)
This paper takes a fresh look at the application of quadratic penalty functions to linear programming. Recently, Madsen et al. (Ref. 1) described a continuation algorithm for linear programming based on smoothing a dual ...
A derivation of Lovász' theta via augmented lagrange duality
(E D P Sciences, 2003)
A recently introduced dualization technique for binary linear programs with equality constraints, essentially due to Poljak et al. , and further developed in Lemar´echal and Oustry , leads to simple alternative ...
Sufficient global optimality conditions for bivalent quadratic optimization
We prove a sufficient global optimality condition for the problem of minimizing a quadratic function subject to quadratic equality constraints where the variables are allowed to take values -1 and 1. We extend the condition ...
Constrained nonlinear programming for volatility estimation with GARCH models
This paper proposes a constrained nonlinear programming view of generalized autoregressive conditional heteroskedasticity (GARCH) volatility estimation models in financial econometrics. These models are usually presented ...
Linear huber M-estimator under ellipsoidal data uncertainty
The purpose of this note is to present a robust counterpart of the Huber estimation problem in the sense of Ben-Tal and Nemirovski when the data elements are subject to ellipsoidal uncertainty. The robust counterparts are ...
On the S-procedure and some variants
We give a concise review and extension of S-procedure that is an instrumental tool in control theory and robust optimization analysis. We also discuss the approximate S-Lemma as well as its applications in robust optimization.
On semidefinite bounds for maximization of a non-convex quadratic objective over the ℓ1 unit ball
(E D P Sciences, 2006)
We consider the non-convex quadratic maximization problem subject to the ℓ1 unit ball constraint. The nature of the l1 norm structure makes this problem extremely hard to analyze, and as a consequence, the same difficulties ...
An exact algorithm for the capacitated vertex p-center problem
We develop a simple and practical exact algorithm for the problem of locating p facilities and assigning clients to them within capacity restrictions in order to minimize the maximum distance between a client and the ...
Parallel image restoration using surrogate constraint methods
(Academic Press, 2007)
When formulated as a system of linear inequalities, the image restoration problem yields huge, unstructured, sparse matrices even for images of small size. To solve the image restoration problem, we use the surrogate ...