需要金幣:![]() ![]() |
資料包括:完整論文 | ![]() |
![]() |
轉(zhuǎn)換比率:金額 X 10=金幣數(shù)量, 例100元=1000金幣 | 論文字?jǐn)?shù):15頁 | ![]() | |
折扣與優(yōu)惠:團(tuán)購最低可5折優(yōu)惠 - 了解詳情 | 論文格式:Word格式(*.doc) | ![]() |
摘要:共軛梯度法是求解非線性無約束優(yōu)化問題的一種重要方法,尤其適用于求解大規(guī)模優(yōu)化問題. 本文提出了一種新的共軛梯度法. 對任意的線性搜索,該方法都滿足充分下降條件. 同時,在Armijo型線搜索下,該算法具有全局收斂性. 關(guān)鍵詞:共軛梯度法;無約束優(yōu)化問題;全局收斂性;Armijo型線搜索
ABSTRACT:Conjugate gradient method is a kind of important method for solving the nonlinear unconstrained optimization problem. It is especially suitable for solving large-scale optimization problem. This paper presents a new conjugate gradient method. The method always generates sufficiently descent direction independent on the line search be used. At the same time, we prove that the method proposed in this paper is global convergence with Armijo type line search. Keywords: conjugate gradient method; unconstrained optimization problem; global convergence; Armijo type line search
目前求解無約束優(yōu)化問題有很多方法,比如最速下降法、牛頓法、擬牛頓法和共軛梯度法.在這些方法中,共軛梯度法是求解大規(guī)模無約束優(yōu)化問題的有效方法之一. 本文提出了求解無約束優(yōu)化問題的一種新的共軛梯度法.對任意的線搜索,該方法都滿足充分下降條件.該方法在Armijo型線搜索下,具有全局收斂性,說明該方法具有一定的有效性.
|