In general, the complexity of synchromodal transport lies in the relation between the possible decisions, and their effect on the performance over time. We consider that a single network-wise LSP decides over all services and transfers even if they are not its own. On the supply side, we consider that all available services and transfers are fixed, but not necessarily the same for each period of the horizon. The number of containers that will arrive each period of the horizon and their characteristics are uncertain, but there is probabilistic information about their arrival (which may vary between periods of the horizon). Containers are characterized by a destination, release-day and due-day. In this paper, we study the problem of scheduling containers in a synchromodal network with the objective of maximizing performance over a multi-period horizon. As a result, there are more consolidation options throughout the network and throughout time than in traditional intermodal transport, making the optimization more challenging. This increased flexibility allows LSPs to select, or to change, the next part of a shipment’s route as late as possible, with the possibility of including the latest information about the transportation network. In synchromodal transport, any service (transportation mode with specific attributes such as schedule, duration, capacity, cost, etc.) and any transfer (change from one service to another in an intermodal terminal) can be used for any shipment (Riessen et al., 2015a). Synchromodal transport is a form of intermodal transport with so-called mode-free booking flexibility, which provides LSPs with network-wide real-time control to maximize the overall efficiency while satisfying agreed conditions such as time, costs, emissions, etc. In intermodal transport, mode choice decisions are made predominately by the shippers and transportation modes are booked in advance by the LSPs (Khakdaman et al., 2020). In this paper, we focus on one of those approaches: synchromodal transport. Increasingly, LSPs are opting for cooperation and integration approaches among different processes for planning and controlling intermodal transport (SteadieSeifi et al., 2014). The organization and synchronization of the various transportation services in an intermodal network can further ease or impede this change. However, economical and environmental benefits are not alone the precursors of a change from road to intermodal transport. The interest of Logistic Service Providers (LSPs) in intermodal transport has increased due to its potential savings in cost (Kordnejad, 2014) and emissions (Craig et al., 2013) compared to road transport.

Sigma as 227 program tv