• Publications
  • Influence
On the implementation of an interior-point filter line-search algorithm for large-scale nonlinear programming
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
An algorithmic framework for convex mixed integer nonlinear programs
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
Nonlinear Programming - Concepts, Algorithms, and Applications to Chemical Processes
  • L. Biegler
  • Computer Science
  • MOS-SIAM Series on Optimization
  • 14 September 2010
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
Systematic Methods of Chemical Process Design
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
Line Search Filter Methods for Nonlinear Programming: Motivation and Global Convergence
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
SIAM Journal on Optimization
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, nonlinearExpand
Failure of global convergence for a class of interior point methods for nonlinear programming
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
An overview of simultaneous strategies for dynamic optimization
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 overExpand
Advances in simultaneous strategies for dynamic process optimization
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 presentExpand
Large-scale nonlinear programming using IPOPT: An integrating framework for enterprise-wide dynamic optimization
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