An ODE-Based Trust Region Filter Algorithm for Unconstrained Optimization
An ODE-Based Trust Region Filter Algorithm for Unconstrained Optimization
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DOI：
10.1080/01630563.2011.563157
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发表时间：
2011-04
影响因子：
1.2
通讯作者：
Yi-gui Ou
中科院分区：
文献类型：
--
作者：
Yi-gui Ou
本文提出了一种基于ode的无约束优化信赖域滤波算法。它可以看作是信任域和过滤技术与基于ode的方法的结合。与现有的信任域滤波方法和基于ode的方法不同，该方法的一个显著特点是在每次迭代时，求解一个简化的线性系统得到一个试步，从而避免了求解信任域子问题。在一定的标准假设下，证明了该算法是全局收敛的。初步的数值结果表明，新算法对大规模问题是有效的。
In this article, an ODE-based trust region filter algorithm for unconstrained optimization is proposed. It can be regarded as a combination of trust region and filter techniques with ODE-based methods. Unlike the existing trust-region-filter methods and ODE-based methods, a distinct feature of this method is that at each iteration, a reduced linear system is solved to obtain a trial step, thus avoiding solving a trust region subproblem. Under some standard assumptions, it is proven that the algorithm is globally convergent. Preliminary numerical results show that the new algorithm is efficient for large scale problems.