This dataset accompanies the following article:
Nicolet, Shobayo, van Hassel, & Atasoy (2023) “An assessment methodology for a modular terminal concept for container barging in seaports”, Case Studies on Transport Policy, 14: 101103.
It also accompanies Chapter 5 of the doctoral thesis of Adrien Nicolet and groups the necessary files to generate the tables and figures contained in the Chapter.

It is composed of the following 16 files:

MMT_timecost.py			solves the time savings optimization problem for a given port (Rotterdam:'NL33' or Antwerp:'BE21'), a given seasonality factor (month_factor or month_factor18), and a given number of modular terminals (fix_NUM)
MMT_modechoice.ipynb		applies the demand model to the situation without and with Modular Mobile Terminal (MMT)
ModeShares_MMT.xlsx		stores the resulting modal shares without and with MMTs
CDSNDP_deter_noMMT.ipynb	applies the supply model to the situation without MMTs
CDSNDP_deter_MMT.ipynb		applies the supply model to the situation with MMTs
Simulation_noMMT.ipynb		performs the out-of-sample simulation of supply model results for the situation without MMTs
Simulation_MMT.ipynb		performs the out-of-sample simulation of supply model results for the situation with MMTs
Competition_noMMT.py		solves the competition model in the situation without MMTs
Competition_MMT.py		solves the competition model in the situation with MMTs
Competition_9n.sh		script to run the files "Competition_noMMT.py" or "Competition_MMT.py"
utility.py			defines the classes Utility and ODpair (Origin-Destination pair)
shipper.py			defines the classes Shipment, Shipper and Population
network.py			defines the classes Services and Network
fleet.py			defines the classes Vessel and Fleet
iwtoperator.py			defines the class IWToperator (Inland Waterway Transport operator)
postprocess.py			allows to write the outcomes of the competition model into an output file