کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
476622 | 1446018 | 2014 | 8 صفحه PDF | دانلود رایگان |
• A unified theory that enables variability ordering for any mean preserving transformation.
• Application to affine transformation and correction of an error in the literature.
• Application to truncation and inventory models in supply chain management.
• Application to capping and procurement risk management.
The stochastic variability measures the degree of uncertainty for random demand and/or price in various operations problems. Its ordering property under mean-preserving transformation allows us to study the impact of demand/price uncertainty on the optimal decisions and the associated objective values. Based on Chebyshev’s algebraic inequality, we provide a general framework for stochastic variability ordering under any mean-preserving transformation that can be parameterized by a single scalar, and apply it to a broad class of specific transformations, including the widely used mean-preserving affine transformation, truncation, and capping. The application to mean-preserving affine transformation rectifies an incorrect proof of an important result in the inventory literature, which has gone unnoticed for more than two decades. The application to mean-preserving truncation addresses inventory strategies in decentralized supply chains, and the application to mean-preserving capping sheds light on using option contracts for procurement risk management.
Journal: European Journal of Operational Research - Volume 239, Issue 3, 16 December 2014, Pages 802–809