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Stochastic Benders decomposition for the supply chain investment planning problem under demand uncertainty

机译:需求不确定条件下供应链投资计划问题的随机Bender分解

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This paper presents the application of a stochastic Benders decomposition algorithm for the problem of supply chain investment planning under uncertainty applied to the petroleum byproducts supply chain. The uncertainty considered is related with the unknown demand levels for oil products. For this purpose, a model was developed based on two-stage stochastic programming. It is proposed two different solution methodologies, one based on the classical cutting plane approach presented by Van Slyke & Wets (1969), and other, based on a multi cut extension of it, firstly introduced by Birge & Louveaux (1988). The methods were evaluated on a real sized case study. Preliminary numerical results obtained from computational experiments are encouraging.
机译:本文提出了一种随机Benders分解算法在不确定性应用于石油副产品供应链的供应链投资计划问题中的应用。所考虑的不确定性与未知的石油产品需求水平有关。为此,基于两阶段随机规划开发了一个模型。提出了两种不同的解决方法,一种是基于Van Slyke&Wets(1969)提出的经典剖切面方法,另一种是基于Birge&Louveaux(1988)首次提出的多切面扩展方法。这些方法在实际案例研究中进行了评估。从计算实验获得的初步数值结果令人鼓舞。

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