A new feasible descent primal-dual interior point algorithm for nonlinear inequality constrained optimization

作者：Jian, Jin bao; Pan, Hua qin^*

来源：Applied Mathematical Modelling, 2010, 34(7): 1952-1963.

DOI：10.1016/j.apm.2009.10.012

• Constrained optimization
• Interior point method
• Working set
• Global convergence
• Superlinear convergence

In this paper, a new feasible primal-dual interior point algorithm for solving inequality constrained optimization problems is presented. At each iteration, the algorithm solves only two or three reduced systems of linear equations with the same coefficient matrix. The searching direction is feasible and the object function is monotone decreasing. The proposed algorithm is proved to possess global and superlinear convergence under mild conditions. Finally, some numerical experiments with the algorithm are reported.

• 出版日期2010-7
• 单位广西大学