等式约束优化的投影拟牛顿法的非单调信赖域算法

摘要

This paper gives a decompose of projected quasi-Newton algorithm in association with nonmonotone trust region for solving nonlinear equality constrained optimization problems.The proposed method is globally convergent even if conditions are mild.In order to assure local superlinear rate and obtain other convergence properties,a second order correction step which brings the iterates closer to the feasible set is described.The correction step allows to prove that the proposed algorithm is also locally superlinear convergent.%提供了分解投影拟牛顿法结合非单调信赖域算法求解非线性等式约束优化问题.在合理的条件下,证明了算法的整体收敛性.通过引进二阶矫正步克服了MARATOS效应,使算法保持了局部超线性收敛速率.