Steepest Descent

Meza, Juan

关键词: 97;    CONVERGENCE;    OPTIMIZATION;    LAWRENCE BERKELEY LABORATORY;   

DOI  :  10.2172/983240
RP-ID  :  LBNL-3395E
PID  :  OSTI ID: 983240
Others  :  TRN: US201014%%592

美国|英语

来源: SciTech Connect

【 摘 要 】

The steepest descent method has a rich history and is one of the simplest and best known methods for minimizing a function. While the method is not commonly used in practice due to its slow convergence rate, understanding the convergence properties of this method can lead to a better understanding of many of the more sophisticated optimization methods. Here, we give a short introduction and discuss some of the advantages and disadvantages of this method. Some recent results on modified versions of the steepest descent method are also discussed.