随机需求下供应链成本优化的随机模型预测控制

Tikito Kawtar, S. Achchab, Y. Benadada
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引用次数: 2

摘要

本文的目的是提出一个随机模型预测控制来优化供应链中的运输和储存成本。目标是在多阶段、多层次的供应链中对随机多产品需求做出响应,使综合成本的目标函数最小化。仿真结果表明,仿射追索随机模型预测控制(arsmpc)具有较好的控制效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Stochastic Model Predictive Control for costs optimization in a supply chain under a stochastic demand
This paper aims to present a Stochastic Model Predictive Control to optimize the costs of shipping and storage in a supply chain. The goal is to minimize the objective function of the combined costs in a multi-stage and a multi-level supply chain responding to a stochastic multi-product demand. The simulation using Matlab provides a comparison between classical models and the proposed model, and shows that the Affine Recourse Stochastic Model Predictive Control - AR SMPC offers better results.
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