Now showing items 1-6 of 6
A Measure of Worst-Case HPerformance and of Largest Acceptable Uncertainty
The structured singular value (SSV or ) is know to be an effective tool for assessing robust performance of linear time- invariant models subject to structured uncertainty. Yet all a single analysis provides is a bound ݠon ...
Nonmonotone Line Search for Minimax Problems
It was recently shown that, in the solution of smooth constrained optimization problems by sequential programming (SQP), the Maratos effect can be prevented by means of a certain nonmonotone (more precisely, four-step ...
User's Guide for FSQP Version 2.0 A Fortran Code for Solving Optimization Problems, Possibly Minimax, with General Inequality Constraints and Linear Equality Constraints, Generating Feasible Iterates
FSQP 2.0 is a set of Fortran subroutines for the minimization of the maximum of a set of smooth objective functions (possibly a single one) subject to nonlinear smooth inequality constraints, linear inequality and linear ...
Fast Feasible Direction Methods, with Engineering Applications
Optimization problems arising in engineering applications often present distinctive features that are not exploited, or not accounted for, in standard numerical optimization algorithms and software codes. First, in many ...
A Note on the Positive Definiteness of BFGS Update in Constrained Optimization
This note reviews a few existing methods to maintain the positive definiteness of BFGS in constrained optimization, and their impacts on both global and local convergence. The boundedness of the matrix from above is also ...
User's Guide for FSQP Version 3.0c: A FORTRAN Code for Solving Constrained Nonlinear (Minimax) Optimization Problems, Generating Iterates Satisfying All Inequality and Linear Constraints
FSQP 3.0c is a set of FORTRAN subroutines for the minimization of the maximum of a set of smooth objective functions (possibly a single one) subject to general smooth constraints. If the initial guess provided by the user ...