13h30 - 13h55
Solving Unconstrained Non-convex Programs Using ACCPM
The analytic center cutting plane method (ACCPM) and proximal ACCPM are well known techniques for solving linear and nonlinear convex programming problems. We propose two sequential convex programming methods based on ACCPM and con- vexification techniques to tackle unconstrained problems with a non-convex objective function.
13h55 - 14h20
Fast Local Convergence of Interior-Point Methods in the Absence of Strict Complementarity
We show that whenever the strict-complementarity assumption fails to be satisfied at a local solution, an appropriate scaling of the primal-dual Lagrange multiplier estimates allows to recover superlinear convergence in interior-point methods for nonlinear optimization.
14h20 - 14h45
Inexact Optimization for Multidisciplinary Aerospace Design
Many optimization problems found in aerospace design contain thousands of design variables and constraints. We present an optimization strategy based on inexact Newton methods for efficiently solving problems of this size. Results from several test problems show the effectiveness of the inexact method compared to an exact strategy.
14h45 - 15h10
Iterative Methods for SQD Linear Systems
Symmetric quasi-definite (SQD) systems arise naturally in
interior-point methods for convex optimization and in some regularized
PDE problems. In this talk we review the connection between SQD linear
systems and other related problems and investigate their iterative