More test examples for nonlinear programming codes
More test examples for nonlinear programming codes
SIAM Journal on Control and Optimization
SIAM Journal on Control and Optimization
A robust sequential quadratic programming method
Mathematical Programming: Series A and B
On combining feasibility, descent and superlinear convergence in inequality constrained optimization
Mathematical Programming: Series A and B
CUTE: constrained and unconstrained testing environment
ACM Transactions on Mathematical Software (TOMS)
Journal of Optimization Theory and Applications
A Computationally Efficient Feasible Sequential Quadratic Programming Algorithm
SIAM Journal on Optimization
On the Constant Positive Linear Dependence Condition and Its Application to SQP Methods
SIAM Journal on Optimization
On the Accurate Identification of Active Constraints
SIAM Journal on Optimization
Globally and superlinearly convergent QP-free algorithm for nonlinear constrained optimization
Journal of Optimization Theory and Applications
A Feasible Sequential Linear Equation Method for Inequality Constrained Optimization
SIAM Journal on Optimization
Journal of Computational and Applied Mathematics
The use of QP-free algorithm in the limit analysis of slope stability
Journal of Computational and Applied Mathematics
An improved infeasible SSLE method for constrained optimization without strict complementarity
Computers and Operations Research
| Hi-index | 7.29 |
In this paper, by means of a new efficient identification technique of active constraints and the method of strongly sub-feasible direction, we propose a new sequential system of linear equations (SSLE) algorithm for solving inequality constrained optimization problems, in which the initial point is arbitrary. At each iteration, we first yield the working set by a pivoting operation and a generalized projection; then, three or four reduced linear equations with a same coefficient are solved to obtain the search direction. After a finite number of iterations, the algorithm can produced a feasible iteration point, and it becomes the method of feasible directions. Moreover, after finitely many iterations, the working set becomes independent of the iterates and is essentially the same as the active set of the KKT point. Under some mild conditions, the proposed algorithm is proved to be globally, strongly and superlinearly convergent. Finally, some preliminary numerical experiments are reported to show that the algorithm is practicable and effective.