Integrated Optimal Design of Multi-echelon Supply Chain Network for Group Enterprise under Demand Uncertainty

H.-l. Pang, Y.-W. Zhou, and B. Hou (PRC)


Demand uncertainty, Multi-echelon supply chain, Stochastic chance-constrained programming, Genetic algorithm


Considering the impact of customers’ demand uncertainty, a problem of optimal supply chain network design for group enterprise was studied in this paper. Putting every component of the supply chain such as suppliers, plants, warehouses, distribution centers and customers into an identical decision system, we presented an integrated optimal design model of multi-products, multi-echelon supply chain network with objective of minimizing operation cost on the condition of maximizing customers’ satisfaction. According to characteristics of the supply chain network, materials transference between different nodes and stochastic chance constraints, a genetic algorithm based on real number genome matrix encoding with stochastic sampling constraints verifying is proposed. Numeric example is performed and the results illustrate that proposed model and algorithm are feasible and effective.

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