论文部分内容阅读
This paper presents a new trust region dogleg method for unconstrained optimization. The method can deal with the case when the Hessian B of quadratic models is indefinite. It is proved that the method is globally convergent and has a quadratic convergence rate if B(k)=Δ2f(x(k)). Under certain conditions, the solution obtained by the method is even a second order stationary point. Numerical results also declare effectiveness of the method.