A robust rolling horizon framework for empty repositioning

Naturally imbalanced freight flows force transportation service providers to reposition empty resources. When constructing empty repositioning plans, the cost of repositioning empty resources needs to be weighed against the cost of corrective actions in case of unavailable resources. This is especially challenging given the uncertainty of future demand. We design and implement a robust rolling horizon framework for constructing effective empty repositioning plans. An extensive computational study demonstrates the benefits of explicitly accounting for uncertainty in future demand by using robust optimization, and pragmatically controlling the level of conservatism in hedging against this uncertainty. We also investigate practical strategies for reducing the complexity of managing the repositioning of empty resources in transportation service networks covering huge geographic areas.