A generalized super-memory gradient projection method of strongly sub-feasible directions with strong convergence for nonlinear inequality constrained optimization.
Jin-Bao JianYou-Fang ZengChun-Ming TangPublished in: Comput. Math. Appl. (2007)
Keyphrases
- constrained optimization
- gradient projection method
- objective function
- stationary points
- feasible solution
- constrained optimization problems
- constraint handling
- penalty function
- augmented lagrangian
- unconstrained optimization
- penalty functions
- inequality constraints
- optimal solution
- global convergence
- multi objective
- convergence rate
- global optimum
- optimization problems
- convergence speed
- nonlinear optimization
- convergence analysis
- interval analysis
- neural network
- lagrange multipliers
- line search
- iterative algorithms
- optimization methods
- linear program
- cost function