Stochastic Model Predictive Control for costs optimization in a supply chain under a stochastic demand
Kawtar Tikito, Saïd Achchab, Youssef Benadada
Abstract
Kawtar Tikito, Saïd Achchab, Youssef Benadada
Abstract
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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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.
Key concepts: Supply chain, Stochastic modelling, Model predictive control, Computer science, Affine transformation, MATLAB, Mathematical optimization, Stochastic optimization