2019 年 29 巻 4 号 p. 8-17
Recently, particular attention has been paid attention to memoryless quasi-Newton methods for solving unconstrained optimization problems. Because memoryless quasi-Newton methods do not need the storage of memories for matrix and their computing cost par a iteration is low, the methods are efficient to large-scale unconstrained optimization problems. Moreover, since the methods are closely related to not only quasi-Newton methods but also nonlinear conjugate gradient methods and nonlinear three-term conjugate gradient method, it is expected that the methods are promising. This paper introduces recent studies on memoryless quasi-Newton methods.