An RQP algorithm using a differentiable exact penalty function for inequality constrained problems

In this paper the authors propose a recursive quadratic programming algorithm for nonlinear programming problems with inequality constraints that uses as merit function a differentiable exact penalty function. The algorithm incorporates an automatic adjustment rule for the selection of the penalty parameter and makes use of an Armijo-type line search procedure that avoids the need to evaluate second order derivatives of the problem functions. The authors prove that the algorithm possesses global and superlinear convergence properties. Numerical results are reported.