### Optimization and Systems Theory Seminar

Friday, December 15, 2000, 11.00-12.00, Room 3721, Lindstedtsv. 25

** Andreas Wächter**

Department of Chemical Engineering

Carnegie Mellon University

Pittsburgh, Pennsylvania

USA

E-mail: andreasw@andrew.cmu.edu

####
An interior point algorithm for large-scale nonlinear programming

A primal-dual interior point algorithm for nonlinear optimization
problems (NLPs) will be presented. The method follows a line search
approach, where the search directions are computed using a
non-orthogonal decomposition scheme. This allows an efficient
exploitation of problem structures as they are encountered in many
chemical engineering applications. We will present numerical results
for dynamic optimization problems, where the NLPs obtained by
discretization using collocation on finite elements have up to 800,000
variables.
In this talk we will discuss the issue of global convergence in more
detail. Many of the current interior point NLP methods can be shown
to fail to converge to a feasible point on a simple, well-posed
problem. We will present a line search procedure, where the
traditional merit function is replaced by the notion of a filter which
has recently been proposed by Fletcher and Leyffer. This method
guarantees convergence to a feasible point, and in numerical tests
seems generally more efficient and robust than our previous merit
function approach.

Calendar of seminars

*Last update: December 6, 2000 by
Anders Forsgren,
anders.forsgren@math.kth.se.
*