Li Xiangrong, Wang Bopeng, Hu Wujie
Guangxi Colleges and Universities Key Laboratory of Mathematics and Its Applications, College of Mathematics and Information Science, Guangxi University, Nanning, Guangxi P.R. China.
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。
