当前位置: X-MOL 学术Optimization › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
An interior point approach for linear complementarity problem using new parametrized kernel function
Optimization ( IF 1.6 ) Pub Date : 2021-06-29 , DOI: 10.1080/02331934.2021.1945051
Ayache Benhadid 1 , Khaled Saoudi 1 , Fateh Merahi 1
Affiliation  

In this paper, we propose a primal–dual interior point method for Linear Complementarity Problem (LCP) based on a new parameterized kernel function. The investigation according to it yields the best-known iteration bound O(nlog(n)log(nϵ)) for large-update algorithm and thus improves the iteration bound obtained in Bai et al. (SIAM J Optim. 2004;15:101–128) for large-update algorithm. Finally, we present few numerical results to demonstrate the efficiency of the proposed algorithm.



中文翻译:

使用新参数化核函数求解线性互补问题的内点法

在本文中,我们提出了一种基于新参数化核函数的线性互补问题 (LCP) 的原始对偶内点法。根据它进行的调查产生了最著名的迭代界限(n日志(n)日志(nε))用于大更新算法,从而改进了 Bai 等人获得的迭代边界。(SIAM J Optim. 2004;15:101–128) 用于大更新算法。最后,我们给出了一些数值结果来证明所提出算法的效率。

更新日期:2021-06-29
down
wechat
bug