A filter-free sequential quadratic programming (SQP) method is presented 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 infeasible 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 numerical results are also presented to show the efficiency of the proposed algorithm.