A comprehensive description of the primal-dual interior-point algorithm with a filter line-search method for nonlinear programming is provided, including the feasibility restoration phase for the filter method, second-order corrections, and inertia correction of the KKT matrix.Expand

A class of hybrid algorithms, of which branch-and-bound and polyhedral outer approximation are the two extreme cases, are proposed and implemented and Computational results that demonstrate the effectiveness of this framework are reported.Expand

The author provides a firm grounding in fundamental NLP properties and algorithms, and relates them to real-world problem classes in process optimization, thus making the material understandable and useful to chemical engineers and experts in mathematical optimization.Expand

This chapter discusses the development of Optimization Theory and Methods for Process Design, and some of the techniques used in this work were new to the literature.Expand

Under mild assumptions it is shown that every limit point of the sequence of iterates generated by the algorithm is feasible, and that there exists at least one limit point that is a stationary point for the problem under consideration.Expand

The SIAM Journal on Optimization contains research articles on the theory and practice of optimization. The areas addressed include linear and quadratic programming, convex programming, nonlinear… Expand

It is shown that a class of interior point methods for general nonlinear programming, including some current methods, is not globally convergent, and those algorithms produce limit points that are neither feasible nor stationary points of some measure of the constraint violation, when applied to a well-posed problem.Expand

Simultaneous approaches for dynamic optimization problems are surveyed and a number of emerging topics are explored. Also known as direct transcription, this approach has a number of advantages over… Expand

Abstract Following on the popularity of dynamic simulation for process systems, dynamic optimization has been identified as an important task for key process applications. In this study, we present… Expand

It is now realistic to solve NLPs on the order of a million variables, for instance, with the IPOPT algorithm, and the recent NLP sensitivity extension to IPopT quickly computes approximate solutions of perturbed NLPs, allowing on-line computations to be drastically reduced.Expand