UPDATING QUASI-NEWTON MATRICES WITH LIMITED STORAGE
UPDATING QUASI-NEWTON MATRICES WITH LIMITED STORAGE
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DOI：
10.1090/s0025-5718-1980-0572855-7
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发表时间：
1980-01-01
影响因子：
2
通讯作者：
NOCEDAL, J
中科院分区：
文献类型：
--
作者：
NOCEDAL, J
研究了如何将BFGS拟牛顿矩阵应用于存储量较大的问题的前提最小化方法。我们给出了一个更新公式，它使用最后m次迭代的信息生成矩阵，其中m是用户提供的任意数字。准牛顿矩阵在每次迭代中通过去掉最旧的信息并用最新的信息代替它来更新。结果表明，所生成的矩阵具有一些理想的性质。所得到的算法进行了数值测试，并与几种已知的方法进行了比较。参考文献
We study how to use the BFGS quasi-Newton matrices to precondition minimization methods for problems where the storage is critical. We give an update formula which generates matrices using information from the last m iterations, where m is any number supplied by the user. The quasi-Newton matrix is updated at every iteration by dropping the oldest information and replacing it by the newest information. It is shown that the matrices generated have some desirable properties. The resulting algorithms are tested numerically and compared with several well-known methods. References