Global linear and local quadratic convergence of a long-step adaptive-mode interior point method for some monotone variational inequality problems

被引:10
作者
Sun, J [1 ]
Zhao, GY
机构
[1] Natl Univ Singapore, Dept Decis Sci, Singapore 119260, Singapore
[2] Natl Univ Singapore, Dept Math, Singapore 119260, Singapore
关键词
polynomial complexity of algorithms; interior point methods; monotone variational inequality problems; rate of convergence;
D O I
10.1137/S1052623496300015
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
An interior point (IP) method is proposed to solve variational inequality problems for monotone functions and polyhedral sets. The method has the following advantages: 1. Given an initial interior feasible solution with duality gap mu(0), the algorithm requires at most O[n log(mu(0)/epsilon)] iterations to obtain an epsilon-optimal solution. 2. The rate of convergence of the duality gap is q-quadratic. 3. At each iteration, a long-step improvement is allowed. 4. The algorithm can automatically transfer from a linear mode to a quadratic mode to accelerate the local convergence.
引用
收藏
页码:123 / 139
页数:17
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