On the Number of Inner Iterations Per Outer Iteration of a Globally Convergent Algorithm for Optimization with General Nonlinear Inequality Constraints and Simple Bounds.
Andrew R. ConnNicholas I. M. GouldPhilippe L. TointPublished in: Comput. Optim. Appl. (1997)
Keyphrases
- optimization algorithm
- globally convergent
- inequality constraints
- computational complexity
- optimal solution
- line search
- worst case
- objective function
- constrained optimization
- global convergence
- optimization method
- equality constraints
- np hard
- dynamic programming
- search space
- cost function
- particle swarm optimization
- special case
- evolutionary algorithm
- combinatorial optimization
- linear systems
- higher dimensional
- feature space
- lower bound
- autocalibration
- nonlinear programming
- step size
- convergence rate
- sufficient conditions