中文摘要：

1引言 本文考虑如下非线性约束优化问题 min f（x） s,t．c（z）≤0，

英文摘要：

A filter-free sequential quadratic programming （SQP） method is pre- sented for nonlinear inequality constrained optimization. The method computes a search direction by solving subproblems based on an exact penalty function and has the important feature of infeasibility detection when it is employed to solve infea- sible instances. Furthermore, in each iteration, the step is selected such that either the value of objective function or the measure of constraint violations is sufficiently reduced. A nonmonotone technique originated from the solution of unconstrained optimization is applied to accelerate the algorithm. Under standard assumptions, global convergence of the proposed algorithm is established. The preliminary num- erical results are also presented to show the efficiency of the proposed algorithm.