Representation of the Swedish transport and logistics system in Samgods v. 1.1.

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Markus Bergquist
Emma Rosklint

The national model for freight transportation in Sweden is called Samgods. The purpose of the model is to provide a tool for forecasting and planning of the transport system. Samgods can be used in policy analysis such as studying the effects of a tax change or a change in transport regulation etc. The aim of this report is to give an overview of how the Swedish transport and logistics system is represented in the Samgods model. Samgods consists of several parts, where the logistics module is the core of the model system. This report describes the setup data needed to run version 1.1 of the Samgods model.

The 35 commodity groups used in the model are based on the 24 groups in the European NST/R- nomenclature. Some commodities are further divided due to their importance for Swedish freight transport and varying logistic properties. Transport demand is described with commodity specific demand matrices for 464 administrative zones inside and outside Sweden. The commodity specific P, C or W zones are split into sub-cells that include firms. The method used to generate the firm to firm flows is to divide the firms at the origin zone and destination zone into three categories according to size.

A range of vehicle and vessel types are used to reflect scale advantages in transporting operations, including loading and unloading. The Samgods model uses six vehicle types for road, 10 for rail, 22 for sea and one for air. In total, 98 pre-defined transport chains are used.

Infrastructure networks are used to generate the level of service (LOS)-matrix data for each vehicle/vessel type providing transport time and, distance and network related infrastructure charges. The logistics costs consist of transport costs (vehicle type specific link costs and node costs) and non-transport costs (commodity specific order costs, storage costs and capital costs in inventory as well as capital costs in transit). For each commodity it is assumed that either the overall logistics costs are optimized or the transport costs are minimized. The model generates a huge amount of output at different levels. All the output files generated are described in the last chapter of this report.

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