Philippe L. Toint

Trust Region Methods

Preface 1. Introduction Part I. Preliminaries: 2. Basic Concepts 3. Basic Analysis and Optimality Conditions 4. Basic Linear Algebra 5. Krylov Subspace Methods Part II. Trust-Re...

CUTEr and SifDec

The initial release of CUTE, a widely used testing environment for optimization software, was described by Bongartz, et al. [1995]. A new version, now known as CUTEr, is present...

Lancelot: A FORTRAN Package for Large-Scale Nonlinear Optimization (Release A)

On the Global Convergence of a Filter--SQP Algorithm

A mechanism for proving global convergence in SQP-filter methods for nonlinear programming (NLP) is described. Such methods are characterized by their use of the dominance conce...

Global Convergence of a Trust-Region SQP-Filter Algorithm for General Nonlinear Programming

A trust-region SQP-filter algorithm of the type introduced by Fletcher and Leyffer [Math. Program., 91 (2002), pp. 239--269] that decomposes the step into its normal and tangent...

A primal-dual trust-region algorithm for non-convex nonlinear programming

Superlinear Convergence of Primal-Dual Interior Point Algorithms for Nonlinear Programming

The local convergence properties of a class of primal-dual interior point methods are analyzed. These methods are designed to minimize a nonlinear, nonconvex, objective function...

Lancelot

Partitioned variable metric updates for large structured optimization problems

Towards an Efficient Sparsity Exploiting Newton Method for Minimization

Local convergence analysis for partitioned quasi-Newton updates

Some numerical results using a sparse matrix updating formula in unconstrained optimization

This paper presents a numerical comparison between algorithms for unconstrained optimization that take account of sparsity in the second derivative matrix of the objective funct...

Numerical experiments with partially separable optimization problems