一个新的锥模型自适应信赖域算法

A new self-adaptive trust region algorithm with a conic model

对无约束最优化问题提出了一类锥模型自适应信赖域算法.信赖域半径的修正采用一个新的自适应调节策略.算法在每步迭代中以当前迭代点的信息以及水平向量信息来调节信赖域半径的大小.在适当的条件下,证明了算法的全局收敛性和Q-二阶收敛性,并且给出了相应的数值结果.

In this paper,a self-adaptive trust region algorithm with a conic model for unconstrained optimization problems is proposed.The trust region radius is updated with a new self-adaptive adjustment strategy.At every iteration,the trust region radius is adjusted by the information at the current point and the level vector information.Under some suitable conditions,the global convergence and Q-quadratic convergence of the new method are proved.Numerical results are also presented.