Stochastic capacity planning and dynamic network design

The present paper proposes a mathematical model and a solution approach to the Stochastic Capacity Planning and Dynamic Network Design Problem. Here, strategic decisions usually comprise developing the necessary capacity - through either incrementing capacity on existing assets (facilities or logistics channels) or establishing new capacity in the form of new assets - in order to satisfy increasing demand. Hence, throughout the planning horizon, decisions on which new assets to establish and where to increment capacity must be taken at minimal cost and in a timely manner. However, when demand varies nonmonotonically, decisions on which assets to temporarily shut down in times of decreasing demand and which of those to reopen when market conditions improve must also be taken into account. We propose a multi-stage stochastic mixed-integer programming approach to the problem as well as a Lagrangian Heuristic procedure to attain reasonably well bounded feasible solutions. The proposed method is evaluated in a Global Mining Supply Chain context which, due to the inherently large capital expenses, could have the outcome of its strategic decision making process significantly improved.