A New SQP-Filter Method for Solving Nonlinear Programming Problems (Journal of Computational Mathematics, 2006)
In [4], Fletcher and Leyffer present a new method that solves nonlinear programming problems without a penalty function by SQP-Filter algorithm. It has attracted much attention due to its good numerical results. In this paper we propose a new SQP-Filter method which can overcome Maratos effect more effectively. We give stricter acceptant criteria when the iterative points are far from the optimal points and looser ones vice-versa. About this new method, the proof of global convergence is also presented under standard assumptions. Numerical results show that our method is efficient.
Keywords: Nonlinear programming; Sequential quadratic programming; Filter; Restoration phase; Maratos affects; Global convergence; Multi-objective optimization; Quadratic programming subproblem.