We study a network design problem inspired by a strategic planning problem encountered in the Hunter Valley Coal Chain. Demand is given in the form of freight that is available from a specific date and has to be transported from multiple origins to a single destination before its deadline. It is possible to temporarily store freight at certain intermediate locations along the way from origins to destination. The objective is to determine minimum-cost capacity expansions required on the links and nodes of the network, if any, so as to be able to transport all freight within its given time windows. A natural mixed integer programming formulation with a daily granularity quickly becomes computationally intractable. We investigate the potential of time aggregation to overcome the computational challenges. By aggregating consecutive time periods, a smaller instance is obtained, which can be solved more easily and provides a lower bound on the optimal value. A carefully designed iterative disaggregation scheme identifies a time aggregation that yields an optimal solution to the original problem. An extensive computational study demonstrates the efficacy of the proposed approach.
20th International Congress on Modelling and Simulation (MODSIM2013). Proceedings of the 20th International Congress on Modelling and Simulation (Adelaide, S.A. 1-6 December, 2013) p. 3281-3287