Algorithms for Constrained Minimization of Smooth Nonlinear Functions

Inhaltsverzeichnis

• The watchdog technique for forcing convergence in algorithms for constrained optimization.
• Reduced quasi-Newton methods with feasibility improvement for nonlinearly constrained optimization.
• A surperlinearly convergent algorithm for constrained optimization problems.
• Computation of the search direction in constrained optimization algorithms.
• A projected Lagrangian algorithm and its implementation for sparse nonlinear constraints.
• On some experiments which delimit the utility of nonlinear programming methods for engineering design.
• Determining feasibility of a set of nonlinear inequality constraints.
• Conjugate gradient methods for linearly constrained nonlinear programming.
• Asymptotic properties of reduction methods applying linearly equality constrained reduced problems.