A NEW SQP-FILTER METHOD FOR SOLVING NONLINEAR PROGRAMMING PROBLEMS

• 来源期刊: 计算数学(英文版)
• 关键词: Nonlinear programming Sequential quadratic programming Filter Restoration phase Maratos affects Global convergence Multi-objective optimization Quadratic programming subproblem.
• 年，卷（期）: 2006,（5）
• 页码范围: 609-634
• 页数: 26页
• 语种: 英文

摘要

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.