A capacity decision support model for synchromodal transport under uncertainty

Abstract

Intermodal transport is the transport of goods in the same loading unit and with multiple modes. The combination of road transport with high-capacity transport modes can lead to more sustainable long-haul freight shipping. A drawback of high-capacity transport modes such as trains and barges is their lower flexibility to uncertain events compared to trucks. This lower flexibility is still a major barrier to the modal switch. Synchromodal transport is an extension of intermodal transport which attempts to resolve this lower flexibility. Under synchromodality, mode-free booking allows LSPs to freely switch freight between available modes, which can lead to more efficient capacity utilisation. This work presents a three-stage decision support model to assist capacity decisions in a synchromodal network under uncertain demand from the perspective of LSPs. Logistics service providers typically book slots on high-capacity transport modes such as trains and barges several months in advance, before complete demand information is available. It is assumed that the number of available capacity that can be booked decreases and becomes more expensive as the delivery date grows nearer. Capacity decisions are a part of service network design (SND) problems. Existing research on SND employs two-stage models to account for stochasticity. In such models, capacity decisions are taken in the first stage before demand is known. Updates are performed in the second stage, at which point it is assumed that complete demand information is available. In reality, LSPs update their transport plan continuously as new information becomes available, instead of waiting until all demand is known. Our proposed model differs from two-stage models by considering a third intermediate stage to more accurately represent real-life decision making. Capacity adjustments can be made during this intermediate stage, where it is assumed that part of the demand is known.