A stochastic optimization model for integrated forward/reverse logistics network design

In this paper, we develop a stochastic programming model for an integrated forward/reverse logistics network design under uncertainty. First, an efficient deterministic mixed integer linear programming model is developed for integrated logistics network design to avoid the sub-optimality caused by the separate design of the forward and reverse networks. Then the stochastic counterpart of the proposed MILP model is developed by using scenario-based stochastic approach Numerical results show the power of the proposed stochastic model in handling data uncertainty (C) 2010 The Society of Manufacturing Engineers Published by Elsevier Ltd. All rights reserved.