A multi-period bi-level stochastic programming with decision dependent uncertainty in supply chains

Abstract

The closed loop supply chain faces some challenges related to the complexity of setting production capacity, maximizing the product architecture modularity and operations scheduling when remanufacturing is included in the supply chain networks. A multi-period bi-level stochastic programming framework is used by setting product architecture modularity design is integrated with supply chain networks design at the upper level and multi-period operations scheduling at the lower level. The result show that supply chain tends to postpone the product architecture modularization until the end of product life is imminent. The bi-level optimization is proven to be good approach to get global optimum of the closed loop supply chain. © 2014 Springer International Publishing.