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Sensitivity analysis of linear programming in the presence of correlation among right-hand side parameters or objective function coefficients

机译:右侧参数或目标函数系数之间存在相关性的线性规划的灵敏度分析

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摘要

In the literature, sensitivity analysis of linear programming (LP) has been widely studied. However, only some very simple and special cases were considered when right-hand side (RHS) parameters or objective function coefficients (OFC) correlate to each other. In the presence of correlation when one parameter changes, other parameters vary, too. Here principal component analysis is used to convert the correlation of the LP homogenous parameters into functional relations. Then, using the derivatives of the functional relations, it is possible to perform classical sensitivity analysis for the LP with correlation among RHS parameters or OFC. The validity of the devised method is corroborated by open literature examples having correlation among homogenous parameters.
机译:在文献中,线性规划(LP)的灵敏度分析已被广泛研究。但是,当右侧(RHS)参数或目标函数系数(OFC)相互关联时,仅考虑一些非常简单和特殊的情况。当一个参数发生变化时,在存在相关性的情况下,其他参数也会变化。这里,主成分分析用于将LP均匀参数的相关性转换为功能关系。然后,使用函数关系的导数,可以对具有RHS参数或OFC之间的相关性的LP进行经典的灵敏度分析。在同质参数之间具有相关性的开放文献实例证实了该方法的有效性。

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