A dwindling filter line search algorithm for nonlinear equality constrained optimization

作者：Gu Chao; Zhu Detong^*

来源：Journal of Systems Science and Complexity, 2015, 28(3): 623-637.

DOI：10.1007/s11424-014-2024-1

• Convergence
• dwindling filter
• line search
• nonlinear optimization
• secant update

This paper proposes a dwindling filter line search algorithm for nonlinear equality constrained optimization. A dwindling filter, which is a modification of the traditional filter, is employed in the algorithm. The envelope of the dwindling filter becomes thinner and thinner as the step size approaches zero. This new algorithm has more flexibility for the acceptance of the trial step and requires less computational costs compared with traditional filter algorithm. The global and local convergence of the proposed algorithm are given under some reasonable conditions. The numerical experiments are reported to show the effectiveness of the dwindling filter algorithm.

• 出版日期2015-6
• 单位上海立信会计金融学院; 上海师范大学