In order to efficiently manage a single echelon supply chain under stochastic disturbance and probabilistic constraints,we propose a stochastic model predictive control(SMPC) framework and implement the Markov Chain M...
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In order to efficiently manage a single echelon supply chain under stochastic disturbance and probabilistic constraints,we propose a stochastic model predictive control(SMPC) framework and implement the Markov Chain Monte Carlo(MCMC) algorithm to solve stochastic programming problems in a receding horizon *** generalized autoregressive conditional heteroskedasticity(GARCH) model is adopted for demand *** results show that the new approaches outperform the standard MPC in mitigating the production fluctuating and reducing the integral absolute error(IAE) of the inventory.
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