数学物理学报(英文版) ›› 2005, Vol. 25 ›› Issue (1): 67-80.
欧宜贵,侯定丕
Department of Mahematics,Hainan Uiniversity,Department of Mahematics, Uiniversity of Science and Technology of China
OU Yi-Gui, HOU Ding-Pi
摘要：
In this paper, a new trust region algorithm for nonlinear equality constrained
LC1 optimization problems is given. It obtains a search direction at each iteration not by
solving a quadratic programming subproblem with a trust region bound, but by solving
a system of linear equations. Since the computational complexity of a QP-Problem is in
general much larger than that of a system of linear equations, this method proposed in
this paper may reduce the computational complexity and hence improve computational
efficiency. Furthermore, it is proved under appropriate assumptions that this algorithm
is globally and super-linearly convergent to a solution of the original problem. Some
numerical examples are reported, showing the proposed algorithm can be beneficial from
a computational point of vie
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