Interior methods are a pervasive feature of the optimization landscape today, but it was not
always so. Although interior-point techniques, primarily in the form of barrier methods, were …

One of the most effective methods for nonlinearly constrained optimization generates steps
by solving quadratic subproblems. This sequential quadratic programming (SQP) approach …

Solving an optimal control or estimation problem is not easy. Pieces of the puzzle are found
scattered throughout many different disciplines. Furthermore, the focus of this book is on …

The design and implementation of a new algorithm for solving large nonlinear programming
problems is described. It follows a barrier approach that employs sequential quadratic …

Just as in its 1st edition, this book starts with illustrations of the ubiquitous character of
optimization, and describes numerical algorithms in a tutorial way. It covers fundamental …

This paper deals with a certain class of optimization methods, based on conservative convex
separable approximations (CCSA), for solving inequality-constrained nonlinear …

Interior methods are an omnipresent, conspicuous feature of the constrained optimization
landscape today, but it was not always so. Primarily in the form of barrier methods, interior …

Line search methods are proposed for nonlinear programming using Fletcher and Leyffer's
filter method [Math. Program., 91 (2002), pp. 239--269], which replaces the traditional merit …

The paper describes an interior-point algorithm for nonconvex nonlinear programming
which is a direct extension of interior-point methods for linear and quadratic programming …

Nonlinear programming (NLP) has become an essential tool in process engineering,
leading to profit gains through improved plant designs and better control strategies. The …