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 find the vbscm an effective factor in sustainability. in this context, supply chain network design has a significant impact on all value drivers (i.e. sales, supply chain costs, fixed 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 finished products) and financial 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 affecting 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.