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 eac...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.展开更多
In this paper, we provide a counter example for a successful method, i.e. IMP-BOT method [6], based on ODE for unconstrained optimization. And we obtainthat methods based on BDF and the general trapezoidal metod for u...In this paper, we provide a counter example for a successful method, i.e. IMP-BOT method [6], based on ODE for unconstrained optimization. And we obtainthat methods based on BDF and the general trapezoidal metod for unconstrainedoptimization is bad efficient because these methods even if have A stability, not Lstability.展开更多
文摘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.
文摘In this paper, we provide a counter example for a successful method, i.e. IMP-BOT method [6], based on ODE for unconstrained optimization. And we obtainthat methods based on BDF and the general trapezoidal metod for unconstrainedoptimization is bad efficient because these methods even if have A stability, not Lstability.
