Journal of the Operations Research Society of China ›› 2013, Vol. 1 ›› Issue (4): 523-536.doi: 10.1007/s40305-013-0031-x
• Continuous Optimization • Previous Articles Next Articles
Online:
Published:
Abstract:
Interior-Point Methods (IPMs) not only are the most effective methods in practice but also have polynomial-time complexity. Many researchers have proposed IPMs for Linear Optimization (LO) and achieved plentiful results. In many cases these methods were extendable for LO to Linear Complementarity Problems (LCPs) successfully. In this paper, motivated by the complexity results for linear optimization based on the study of H. Mansouri et al. (Mansouri and Zangiabadi in J. Optim. 62(2):285–297, 2013), we extend their idea for LO to LCP. The proposed algorithm requires two types of full-Newton steps are called, feasibility steps and (ordinary) centering steps, respectively. At each iteration both feasibility and optimality are reduced exactly at the same rate. In each iteration of the algorithm we use the largest possible barrier parameter value θ which lies between the two values 1 17n and 1 13n , this makes the algorithm faster convergent for problems having a strictly complementarity solution.
Hossein Mansouri · Mohammad Pirhaji. An Adaptive Infeasible Interior-Point Algorithm for Linear Complementarity Problems[J]. Journal of the Operations Research Society of China, 2013, 1(4): 523-536.
0 / / Recommend
Add to citation manager EndNote|Reference Manager|ProCite|BibTeX|RefWorks
URL: https://www.jorsc.shu.edu.cn/EN/10.1007/s40305-013-0031-x
https://www.jorsc.shu.edu.cn/EN/Y2013/V1/I4/523