A nonmonotone trust-region line search method for large-scale unconstrained optimization

详细信息    查看全文

• 作者：Masoud  ; Ahookhosh^a ;   ; ^{ahoo.math@gmail.com} ; Keyvan  ; Amini^a ;   ; ^{kamini@razi.ac.ir} ; Mohammad Reza  ; Peyghami^b ;   ; ^{peyghami@kntu.ac.ir}
• 关键词：Unconstrained optimization ; Trust-region method ; Armijo-type line search ; Nonmonotone technique
• 刊名：Applied Mathematical Modelling
• 出版年：2012
• 出版时间：January 2012
• 年：2012
• 卷：36
• 期：1
• 页码：478-487
• 全文大小：249 K

文摘

We consider an efficient trust-region framework which employs a new nonmonotone line search technique for unconstrained optimization problems. Unlike the traditional nonmonotone trust-region method, our proposed algorithm avoids resolving the subproblem whenever a trial step is rejected. Instead, it performs a nonmonotone Armijo-type line search in direction of the rejected trial step to construct a new point. Theoretical analysis indicates that the new approach preserves the global convergence to the first-order critical points under classical assumptions. Moreover, superlinear and quadratic convergence are established under suitable conditions. Numerical experiments show the efficiency and effectiveness of the proposed approach for solving unconstrained optimization problems.