The analytic center cutting plane method and its proximal variant are well known techniques for solving convex programming problems. We propose two seq...

We consider a class of infeasible, path-following methods for convex quadratric programming. Our methods are designed to be effective for solving both nonde...

In this article we address the model order reduction problem for resistor networks by using methods from graph theory. We formulate this problem through gr...

We propose an interior-point algorithm based on an elastic formulation of the \(\ell_1\)-penalty merit function for mathematical programs with complementar...

Interior-point methods in augmented form for linear and convex quadratic programming require the solution of a sequence of symmetric indefinite linear ...

Parameterizing source code for architecture-bound optimization is a common approach to high-performance programming but one that makes the programmer's task ...

Accurate measurements of snow water equivalent (SWE) is an important factor in managing water resources for hydroelectric power generation. SWE over a catchm...

We propose a modified primal-dual interior-point method for nonlinear programming that relaxes the requirement of closely following the central path and lend...

During alloy and process design, it is often desired to identify regions of design or process variables for which certain calculated functions have optimal v...

The present paper describes the coupling of the Mesh Adaptive Direct Search (MADS) algorithm with the FactSage thermochemical software, which allows to calcu...

The paper proposes a framework for sensitivity analyses of blackbox constrained optimization problems for which Lagrange multipliers are not available. Two s...

We propose a new approach to construct adaptive multiscale orthonormal (AMO) bases of R^<i>N</i> that provide highly sparse signal representations....

A mixed interior/exterior-point method for nonlinear programming is described, that handles constraints by way of an <i>l</i>₁-penalty function. A...

An automatic method for constructing linear relaxations of constrained global optimization problems is proposed. Such a construction is based on affine and i...

We introduce the OPAL framework in which the identification of good algorithmic parameters is interpreted as a black box optimization problem whose variables...

Recent advances in coupling novel optimization methods to large-scale computing problems have opened the door to tackling a diverse set of physically realist...

This intentionally short tutorial is an introduction to the main features of AMPL that are relevant to nonlinear optimization model authoring. Pointers are g...

This work analyzes constrained black box optimization in which the functions defining the problem are periodic with respect to some or all the variables. We ...

This work studies multi-objective optimization <i>(MOP)</i> of nonsmooth functions subject to general constraints. We first present definitions and optimalit...

<p>The class of Mesh Adaptive Direct Search (MADS) algorithms is designed for the optimization of constrained black-box problems. The purpose of this paper i...