A strategy for global convergence in a sequential quadratic programming algorithm
SIAM Journal on Numerical Analysis
On combining feasibility, descent and superlinear convergence in inequality constrained optimization
Mathematical Programming: Series A and B
An SQP method for general nonlinear programs using only equality constrained subproblems
Mathematical Programming: Series A and B
A Computationally Efficient Feasible Sequential Quadratic Programming Algorithm
SIAM Journal on Optimization
Globally and superlinearly convergent QP-free algorithm for nonlinear constrained optimization
Journal of Optimization Theory and Applications
Computers & Mathematics with Applications
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This paper is concerned with an improved feasible sequential quadratic programming (FSQP) method which solves an inequality constrained nonlinear optimization problem. As compared with the existing SQP methods, at each iteration of our method, the base direction is only necessary to solve a equality constrained quadratic programming, the feasible direction and the high-order revised direction which avoids Maratos effect are obtained by explicit formulas. Furthermore, the global and superlinear convergence are proved under some suitable conditions.