A two-stage stochastic programming model for value-based supply chain network design

Nowadays, Value-based Supply Chain Management (VbSCM) is considered a resource of competitive advantages, and companies with long term strategic plans nd the VbSCM an eective factor in sustainability. In this context, supply chain network design has a signicant impact on all value drivers (i.e. sales, supply chain costs, xed assets and working capital). This paper proposes a stochastic mixed integer linear programming model for a value-based supply chain network design in which decisions on physical ow (raw materials and nished products) and nancial ow are integrated. The proposed model is designed for a four-echelon, multi-commodity, multi-period supply chain, and it maximizes the value of the company, based on the economic value-added concept, by making some strategic and tactical decisions aecting the value drivers. Furthermore, a scenario-based two-stage stochastic programming model is developed with a scenario generation method based on Nataf transformation. Also, a computational analysis is undertaken to illustrate the performance of the proposed approach