Total variation bounds on the expectation of periodic functions with applications to recourse approximations

成果类型:
Article
署名作者:
Romeijnders, Ward; van der Vlerk, Maarten H.; Haneveld, Willem K. Klein
署名单位:
University of Groningen
刊物名称:
MATHEMATICAL PROGRAMMING
ISSN/ISSBN:
0025-5610
DOI:
10.1007/s10107-014-0829-2
发表日期:
2016
页码:
3-46
关键词:
stochastic-programming problems simple integer recourse convex approximations scenario reduction linear-programs models algorithms optimization
摘要:
We derive a lower and upper bound for the expectation of periodic functions, depending on the total variation of the probability density function of the underlying random variable. Using worst-case analysis we derive tighter bounds for functions that are periodically monotone. These bounds can be used to evaluate the performance of approximations for both continuous and integer recourse models. In this paper, we introduce a new convex approximation for totally unimodular recourse models, and we show that this convex approximation has the best worst-case error bound possible, improving previous bounds with a factor 2. Moreover, we use similar analysis to derive error bounds for two types of discrete approximations of continuous recourse models with continuous random variables. Furthermore, we derive a tractable Lipschitz constant for pure integer recourse models.
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