This book on unconstrained and bound constrained optimization can be used as a tutorial
for self-study or a reference by those who solve such problems in their work. It can also …

This book provides a comprehensive treatment of a very successful class of methods for
solving optimization problems with PDE and inequality constraints as well as variational …

We analyze a trust region version of Newton's method for bound-constrained problems. Our
approach relies on the geometry of the feasible set, not on the particular representation in …

An active set algorithm (ASA) for box constrained optimization is developed. The algorithm
consists of a nonmonotone gradient projection step, an unconstrained optimization step, and …

In this paper, the filter technique of Fletcher and Leyffer (1997) is used to globalize the
primal-dual interior-point algorithm for nonlinear programming, avoiding the use of merit …

Recent developments in numerical methods for solving large differentiable nonlinear
optimization problems are reviewed. State-of-the-art algorithms for solving unconstrained …

The problem of negative variance components is probable to occur in many geodetic
applications. This problem can be avoided if non-negativity constraints on variance …

We develop and analyze a class of trust-region methods for bound-constrained semismooth
systems of equations. The algorithm is based on a simply constrained differentiable …

This article is about numerical methods for the solution of nonlinear equations. We consider
both the fixed-point form and explain why both versions are necessary to understand the …

A central theme of applied mathematics is the design of accurate mathematical models for a
variety of technical, financial, medical, and many other applications, and the development of …