凸约束优化问题的带记忆模型信赖域算法

本文我们考虑求解凸约束优化问题的信赖域方法 .与传统的方法不同 ,我们信赖域子问题的逼近模型中包括过去迭代点的信息 ,该模型使我们可以从更全局的角度来求得信赖域试探步 ,从而避免了传统信赖域方法中试探步的求取完全依赖于当前点的信息而过于局部化的困难 .全局收敛性的获得是依靠非单调技术来保证的

A Trust Region Algorithm with Memory Model for Convex Constrained Optimization

In this paper, we develop a trust region algorithm for convex constrained optimizationproblems. Different from the traditional trust region algorithms, our trust region model includesmemory of the past iteration, which makes the algorithm more farsighted in the sense that its behav-ior is not completely dominated by the local nature of the objective function. We present a nonmono-tone algorithm that has this feature and prove its global convergence under suitable conditions.