对于无约束优化问题,提出了一类新的三项记忆梯度算法.这类算法是在参数满足某些假设的条件下,确定它的取值范围,从而保证三项记忆梯度方向是使目标函数充分下降的方向.在非单调步长搜索下讨论了算法的全局收敛性.为了得到具有更好收敛性质的算法,结合Solodov and Svaiter(2000)中的部分技巧,提出了一种新的记忆梯度投影算法,并证明了该算法在函数伪凸的情况下具有整体收敛性.
In this paper, we propose a new kind of three-term memory gradient method for unconstrained optimization problem. We discuss the global convergence property of the method with non-monotone line search technique. At the same time, a new kind of memory gradient projection method is also presented. The convergence property in the sense that the whole sequence of iterates converges to a solution of the problem is proved under no assumption other than pseudo-convexity and continuous differentiability of f(*).