Title :
Stochastic Model Predictive Control for costs optimization in a supply chain under a stochastic demand
Author :
Kawtar, Tikito ; Said, Amir ; Youssef, Benadada
Author_Institution :
Ecole Nat. Super. d´Inf. et d´Anal. des Syst. (ENSIAS), Mohammed V Univ., Rabat, Morocco
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.
Keywords :
predictive control; production control; stochastic systems; supply chains; AR SMPC; Matlab; affine recourse stochastic model predictive control; costs optimization; multilevel supply chain; multistage chain; stochastic multiproduct demand; History; Mathematical model; Optimization; Predictive control; Predictive models; Stochastic processes; Supply chains; Stochastic Model Predictive Control; Supply chain; optimization of costs; stochastic demand;
Conference_Titel :
Logistics and Operations Management (GOL), 2014 International Conference on
Conference_Location :
Rabat
Print_ISBN :
978-1-4799-4651-8
DOI :
10.1109/GOL.2014.6887436