At the ETC 2005, the specification of a logistics model, that is to become one of the components of the national freight transport model systems of Norway and Sweden, was presented. This model has since been implemented and will be calibrated to aggregate data in the first months of 2007. In 2005/2006, a prototype version of the logistics model was developed, that uses Swedish and Norwegian network and cost data and data on the locations of distribution centres. The parameters of this prototype were not calibrated to observed data. The purpose of this version was mainly to show the feasibility of the approach. Having shown that the approach was feasible, a new and extended version of the logistics model has been specified and applied for both Norway and Sweden within the framework of their national freight transport forecasting systems. The Norwegian model takes as inputs commodity flows from production to consumption zone (that also include the wholesale function). The logistics model then disaggregates these flows to firm-to-firm flows. For Sweden the disaggregation to firm-to-firm flows is done as part of the base matrix calculation, outside the logistics model, and the logistics model takes these as given. After this disaggregation, for both countries, the logistics decisions (shipment size, use of consolidation and distribution centres, mode and vehicle/vessel type and loading unit type choice) are simulated at the firm-to-firm level (micro-simulation). The output of the model consists of flows between origins and destinations (OD-level), where consolidation and distribution centres (including ports, airports and railway terminals) are also treated as origins and destinations. Furthermore, the model can provide information on total logistics cost between zones, which can be used in trade or spatial interaction models. Key features of the new version of the logistics model are: for Norway the model uses all firm-to-firm relations in simulation, for Sweden it is applied for a firm-to-firm relation within sub-cells defined by firm size classes and uses expansion factors to represent the total population; the transport chain generation program within the logistics model includes determining the optimal transfer locations within available transport chains for all modes; in the determination of shipment size the effect of economies of scale in transport (a force leading to larger shipment sizes, because these have lower transport cost) is included. The degree of consolidation (or the load factor of the vehicles) between consolidation centres and distribution centres is determined in an iterative procedure which starts with an assumed average load factor, but in a subsequent iteration includes information on the availability of other cargo (based on the available transport chains and port statistics), and in a further iteration uses the flows between consolidation centres predicted in the previous model iteration. Estimation of a random utility-based logistics model on disaggregate data (partly available, partly still to be collected) is foreseen for future years for both countries. The basic mechanism in the model is minimisation of a deterministic total annual logistics cost function. A procedure to calibrate parameters in the cost function to available aggregate data was developed. The paper includes the structure of the model, highlighting the features added after 2005, explains the calibration procedure and present calibration results. For the covering abstract see ITRD E137145.
Abstract