TY - JOUR A2 - Júdice, Joaquim J. AU - Zhang, Jianguo AU - Xiao, Yunhai AU - Wei, Zengxin PY - 2009 DA - 2009/07/01 TI - Nonlinear Conjugate Gradient Methods with Sufficient Descent Condition for Large-Scale Unconstrained Optimization SP - 243290 VL - 2009 AB - Two nonlinear conjugate gradient-type methods for solving unconstrained optimization problems are proposed. An attractive property of the methods, is that, without any line search,the generated directions always descend. Under some mild conditions, global convergence results forboth methods are established. Preliminary numerical results show that these proposed methods arepromising, and competitive with the well-known PRP method. SN - 1024-123X UR - https://doi.org/10.1155/2009/243290 DO - 10.1155/2009/243290 JF - Mathematical Problems in Engineering PB - Hindawi Publishing Corporation KW - ER -