A multi-stage stochastic optimization model for robust logistics network design

In the last decade, the concern about significant changes in the business environment has led in designing the robust supply chain networks. This paper proposes a multi-stage stochastic programming model for supply chain network design (SCND). Firstly, a deterministic mixed integer linear programming (MILP) model that is able to consider capacity expansion for network facilities as well as different transportation modes beside the traditional features of SCND problem is developed. Secondly, the stochastic counterpart of the proposed deterministic model is developed by using scenario-based multi-stage stochastic programming approach. Numerical results show the efficiency of the proposed stochastic programming model in handling uncertainty resulted from uncertain nature of input parameters.

Keywords:

Robust Facility location , Multi-stage stochastic programming , Supply chain network design