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Strong Stability Preserving General Linear Methods with Runge-Kutta Stability

机译:具有Runge-Kutta稳定性的强稳定性保持一般线性方法

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摘要

We investigate strong stability preserving (SSP) general linear methods (GLMs) for systems of ordinary differential equations. Such methods are obtained by the solution of the minimization problems with nonlinear inequality constrains, corresponding to the SSP property of these methods, and equality constrains, corresponding to order and stage order conditions. These minimization problems were solved by the sequential quadratic programming algorithm implemented in MATLAB (R) subroutine fmincon.m starting with many random guesses. Examples of transformed SSP GLMs of order p = 1, 2, 3, and 4, and stage order q = p have been determined, and suitable starting and finishing procedures have been constructed. The numerical experiments performed on a set of test problems have shown that transformed SSP GLMs constructed in this paper are more accurate than transformed SSP DIMSIMs and SSP Runge-Kutta methods of the same order.
机译:我们研究常微分方程系统的强稳定性保持(SSP)通用线性方法(GLM)。通过求解具有非线性不等式约束(对应于这些方法的SSP属性)以及等式约束(对应于阶次和阶段有序条件)的最小化问题的解决方案,获得了这些方法。这些最小化问题是通过在MATLAB(R)子例程fmincon.m中实现的顺序二次编程算法解决的,该算法从许多随机猜测开始。已经确定了阶数为p = 1、2、3和4且阶段阶数为q = p的转换SSP GLM的示例,并且已构建了合适的开始和完成过程。对一组测试问题进行的数值实验表明,本文构造的转换SSP GLM比相同阶数的转换SSP DIMSIM和SSP Runge-Kutta方法更准确。

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