一种用于无约束优化的改进非单调BFGS算法。
A modified nonmonotone BFGS algorithm for unconstrained optimization.
作者信息
Li Xiangrong, Wang Bopeng, Hu Wujie
机构信息
Guangxi Colleges and Universities Key Laboratory of Mathematics and Its Applications, College of Mathematics and Information Science, Guangxi University, Nanning, Guangxi P.R. China.
出版信息
J Inequal Appl. 2017;2017(1):183. doi: 10.1186/s13660-017-1453-5. Epub 2017 Aug 9.
In this paper, a modified BFGS algorithm is proposed for unconstrained optimization. The proposed algorithm has the following properties: (i) a nonmonotone line search technique is used to obtain the step size [Formula: see text] to improve the effectiveness of the algorithm; (ii) the algorithm possesses not only global convergence but also superlinear convergence for generally convex functions; (iii) the algorithm produces better numerical results than those of the normal BFGS method.
本文提出了一种用于无约束优化的改进BFGS算法。该算法具有以下性质：(i)采用非单调线搜索技术来获得步长[公式：见原文]以提高算法的有效性；(ii)该算法不仅具有全局收敛性，而且对于一般凸函数具有超线性收敛性；(iii)该算法产生的数值结果比普通BFGS方法的结果更好。
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