A strongly sub-feasible primal-dual quasi interior-point algorithm for nonlinear inequality constrained optimization.
Jin-Bao JianHua-Qin PanChun-Ming TangJian-Ling LiPublished in: Appl. Math. Comput. (2015)
Keyphrases
- constrained optimization
- interior point algorithm
- primal dual
- linear programming
- interior point methods
- convex optimization
- objective function
- linear program
- feasible solution
- approximation algorithms
- linear programming problems
- convergence rate
- augmented lagrangian
- variational inequalities
- penalty function
- semidefinite programming
- constrained optimization problems
- simplex method
- algorithm for linear programming
- multicriteria optimization
- linear systems
- convex functions
- line search
- image segmentation
- inequality constraints