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首页> 外文期刊>Journal of Optimization Theory and Applications >Combining Trust-Region Techniques and Rosenbrock Methods to Compute Stationary Points
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Combining Trust-Region Techniques and Rosenbrock Methods to Compute Stationary Points

机译:结合信任区域技术和Rosenbrock方法计算固定点

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摘要

Rosenbrock methods are popular for solving a stiff initial-value problem of ordinary differential equations. One advantage is that there is no need to solve a nonlinear equation at every iteration, as compared with other implicit methods such as backward difference formulas or implicit Runge–Kutta methods. In this article, we introduce a trust-region technique to select the time steps of a second-order Rosenbrock method for a special initial-value problem, namely, a gradient system obtained from an unconstrained optimization problem. The technique is different from the local error approach. Both local and global convergence properties of the new method for solving an equilibrium point of the gradient system are addressed. Finally, some promising numerical results are also presented.
机译:Rosenbrock方法普遍用于解决常微分方程的刚性初值问题。一个优点是,与其他隐式方法(例如,后向差分公式或隐式Runge-Kutta方法)相比,无需在每次迭代时求解非线性方程。在本文中,我们介绍了一种信任区域技术,用于针对特殊的初值问题(即从无约束优化问题获得的梯度系统)选择二阶Rosenbrock方法的时间步长。该技术不同于本地错误方法。提出了求解梯度系统平衡点的新方法的局部和全局收敛特性。最后,给出了一些有希望的数值结果。

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