This directory contains the input and output data of the (adapted) Berlin Food Retailing scenario.
- with range restriction ("DC") for electric vehicles
- without range restriction ("DCoff") for electric vehicles

For both, there are several runs, with ICEV (diesel) and BEV (electric)( vehicles available -> The carrier can choose its fleet composition by solving the VehicleRoutingProblem.

Additionally, there is a tac on CO2eq added for diesel, which will increase the variable costs per m. This tax goes from 9 ups to 300 (noTax ... Tax300)

All runs are solved with setting the maximum number of jsprit iterations to 10 000. 

The run 21a / 71a is a reference case, where only diesel trucks are available and no additional tax is applied.

For further information, please refer to 
VSPWP 20-12: R. Ewert, K. Martins-Turner, C. Thaller, K. Nagel; Using a route-based and vehicle type specific range constraint for improving vehicle routing problems with electric vehicles

and /or  

VSPWP 19-19: K. Martins-Turner, A. Grahle, K. Nagel, D. Göhlich; Electrification of Urban Freight Transport - a Case Study of the Food Retailing Industry; Procedia Computer Science, Volume 170, 2020, 757-763 

KMT: 19.01.2024
For more current studies I suggest to use the network with the correct CRS: see 
"https://svn.vsp.tu-berlin.de/repos/public-svn/matsim/scenarios/countries/de/berlin/berlin-v5.5-10pct/output-berlinv5.5/berlin-v5.5.3-10pct.output_network.xml.gz"
And add the following line to <our code: 
config.global().setCoordinateSystem("EPSG:31468");