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SINGLY DIAGONALLY IMPLICIT RUNGE-KUTTA METHODS COMBINING LINE SEARCH TECHNIQUES FOR UNCONSTRAINED OPTIMIZATION

机译:单对角隐式Runge-Kutta方法结合线搜索技术实现无约束优化

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摘要

There exists a strong connection between numerical methods for the integration of ordinary differential equations and optimization problems. In this paper, we try to discover further their links. And we transform unconstrained problems to the equivalent ordinary differential equations and construct the LRKOPT method to solve them by combining the second order singly diagonally implicit Runge-Kutta formulas and line search techniques. Moreover we analyze the global convergence and the local convergence of the LRKOPT method. Promising numerical results are also reported.
机译:求解常微分方程的数值方法与优化问题之间存在密切的联系。在本文中,我们尝试进一步发现它们的链接。然后,我们将无约束问题转化为等效的常微分方程,并通过结合二阶单对角隐式Runge-Kutta公式和线搜索技术,构造了LRKOPT方法来求解它们。此外,我们分析了LRKOPT方法的全局收敛性和局部收敛性。还报告了有希望的数值结果。

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