Interior-point algorithm for linear optimization based on a new trigonometric kernel function

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• 作者：Xin Li ^{sxlixin12@126.com" class="auth_mail" title="E-mail the corresponding author} ; Mingwang Zhang ; ^{zmwang@ctgu.edu.cn" class="auth_mail" title="E-mail the corresponding author}
• 关键词：Linear optimization ; Kernel function ; Interior-point algorithm ; Large-update ; Polynomial complexity
• 刊名：Operations Research Letters
• 出版年：2015
• 出版时间：September 2015
• 年：2015
• 卷：43
• 期：5
• 页码：471-475
• 全文大小：415 K

文摘

In this paper, we present a new primal–dual interior-point algorithm for linear optimization based on a trigonometric kernel function. By simple analysis, we derive the worst case complexity for a large-update primal–dual interior-point method based on this kernel function. This complexity estimate improves a result from El Ghami et al. (2012) and matches the one obtained in Reza Peza Peyghami et al. (2014).