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Higher-order total variation bounds for expectations of periodic functions and simple integer recourse approximations

机译:期望周期函数和简单整数追索近似的高阶总变化范围

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We derive bounds on the expectation of a class of periodic functions using the total variations of higher-order derivatives of the underlying probability density function. These bounds are a strict improvement over those of Romeijnders et al. (Math Program 157:3–46, 2016b), and we use them to derive error bounds for convex approximations of simple integer recourse models. In fact, we obtain a hierarchy of error bounds that become tighter if the total variations of additional higher-order derivatives are taken into account. Moreover, each error bound decreases if these total variations become smaller. The improved bounds may be used to derive tighter error bounds for convex approximations of more general recourse models involving integer decision variables.
机译:我们使用基础概率密度函数的高阶导数的总变化得出一类周期函数的期望范围。这些界限是对Romeijnders等人的界限的严格改进。 (数学计划157:3-46,2016b),我们使用它们来推导简单整数资源模型的凸近似的误差范围。实际上,如果考虑到其他高阶导数的总变化,我们将获得错误边界的层次结构,该层次将变得更加严格。此外,如果这些总变化变小,则每个误差范围都会减小。改进的界限可用于为涉及整数决策变量的更通用的追索模型的凸近似推导更严格的误差界限。

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