摘要
通过将传统的信赖域算法和非单调Wolfe线搜索结合,提出了一类新的求解无约束优化问题的信赖域算法.新算法给出了新的Wolfe步长准则,通过新的Wolfe步长准则可选择一个较大的步长,这样就减少了算法迭代的次数,提高了算法的有效性;并在一定的条件下,证明了算法的全局收敛性.
We propose a new family of region algorithms for unconstrained optimization problems which is combining traditional trust region method with a non-monotone Wolfe line search technique. A new algorithm that possibly chooses a larger step-length. This can decrease the number of iterations and can improve the efficiency of the algorithms. The global convergence of the algorithms is proved under certain conditions.
出处
《滨州学院学报》
2012年第6期77-83,共7页
Journal of Binzhou University
基金
国家自然科学基金资助项目(11171180)
关键词
信赖域算法
非单调线搜索
全局收敛
trust-region method ~ non-monotone line search
global convergence