摘要
In this paper,a new trust region algorithm for unconstrained LC^1 optimization problems is given.Compare with those existing trust regiion methods,this algorithm has a different feature:it obtains a stepsize at each iteration not by soloving a quadratic subproblem with a trust region bound,but by solving a system of linear equations.Thus it reduces computational complexity and improves computation efficlency,It is proven that this algorithm is globally convergent and locally superlinear under some conditions.
In this paper, a new trust region algorithm for unconstrained LC1 optimization problems is given. Compare with those existing trust regiion methods, this algorithm has a different feature: it obtains a stepsize at each iteration not by soloving a quadratic subproblem with a trust region bound, but by solving a system of linear equations. Thus it reduces computational complexity and improves computation efficiency. It is proven that this algorithm is globally convergent and locally superlinear under some conditions.
