A new constraint qualification condition
Journal of Optimization Theory and Applications
A recursive quadratic programming algorithm that uses differentiable exact penalty functions
Mathematical Programming: Series A and B
A strategy for global convergence in a sequential quadratic programming algorithm
SIAM Journal on Numerical Analysis
A tool for the analysis of Quasi-Newton methods with application to unconstrained minimization
SIAM Journal on Numerical Analysis
Exact penalty function algorithm with simple updating of the penalty parameter
Journal of Optimization Theory and Applications
An exact penalization viewpoint of constrained optimization
SIAM Journal on Control and Optimization
An analysis of reduced Hessian methods for constrained optimization
Mathematical Programming: Series A and B
Superlinear Convergence of a Stabilized SQP Method to a Degenerate Solution
Computational Optimization and Applications
Modified Wilson'S Method for Nonlinear Programswith Nonunique Multipliers
Mathematics of Operations Research
Practical Update Criteria for Reduced Hessian SQP: Global Analysis
SIAM Journal on Optimization
On the Global Convergence of the BFGS Method for Nonconvex Unconstrained Optimization Problems
SIAM Journal on Optimization
Degenerate Nonlinear Programming with a Quadratic Growth Condition
SIAM Journal on Optimization
Modifying SQP for Degenerate Problems
SIAM Journal on Optimization
On the Sequential Quadratically Constrained Quadratic Programming Methods
Mathematics of Operations Research
A practical update criterion for SQP method
Optimization Methods & Software
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This paper develops a reduced Hessian method for solving inequality constrained optimization problems. At each iteration, the proposed method solves a quadratic subproblem which is always feasible by introducing a slack variable to generate a search direction and then computes the steplength by adopting a standard line search along the direction through employing the l 驴 penalty function. And a new update criterion is proposed to generate the quasi-Newton matrices, whose dimensions may be variable, approximating the reduced Hessian of the Lagrangian. The global convergence is established under mild conditions. Moreover, local R-linear and superlinear convergence are shown under certain conditions.