A two-stage stochastic programming approach for value-based closed-loop supply chain network design

The ultimate goal for almost all companies in the current business world is to increase their value; therefore, managers concentrate their efforts on the control of value drivers. This research develops a two-stage stochastic programming model for the value-based supply chain network design, where all parts of a supply chain are configured and controlled in such a way that the total value of the company increases. The proposed model is a three-echelon, multi-commodity, and multi-period model for the tactical and strategic decision making. Also, a comprehensive computational analysis is conducted to evaluate the performance of the proposed approach.