A descent nonlinear conjugate gradient method for large-scale unconstrained optimization

作者：Yu, Gaohang^*; Zhao, Yanlin; Wei, Zengxin

来源：Applied Mathematics and Computation, 2007, 187(2): 636-643.

DOI：10.1016/j.amc.2006.08.087

• unconstrained optimization
• large-scale optimization
• conjugate gradient method
• Wolfe conditions
• global convergence

In this paper, a new nonlinear conjugate gradient method was proposed for large-scale unconstrained optimization which possesses the following three properties: (i) the sufficient descent property holds without any line searches; (ii) employing some steplength technique which ensures the Zoutendijk condition to be held, this method is globally convergent; (iii) this method inherits an important property of the Polak-Ribiere-Polyak (PRP) method: the tendency to turn towards the steepest descent direction if a small step is generated away from the solution, preventing a sequence of tiny steps from happening. Preliminary numerical results show that this method is very promising.

• 出版日期2007-4-15
• 单位中山大学; 广西大学