A globally convergent SQP method for semi-infinite nonlinear optimization
In the paper under review a new method for nonlinear semi-infinite optimization is presented. The method belongs to the class of successive quadratic programming (SQP) methods with trust region technique and utilizes an exact \(L_{\infty}\) penalty function. The algorithm developed is proved to be globally convergent under some assumptions. Implementation hints and some results of numerical experiments are presented, too.
scientific article; zbMATH DE number 4123534
scientific article