Integrated Scheduling Optimization for Railway Feeder Services in the Port of Rotterdam
A game-theoretic approach to incentivising horizontal cooperation
R.J.M. Heemskerk (TU Delft - Mechanical Engineering)
F. Schulte – Mentor (TU Delft - Mechanical Engineering)
R.R. Negenborn – Mentor (TU Delft - Mechanical Engineering)
X. Tang – Graduation committee member (TU Delft - Mechanical Engineering)
M. Wisse – Graduation committee member (TU Delft - Mechanical Engineering)
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Abstract
The need for international transport of goods has increased for decennia, due to the globalisation of supply chains. The impact on the environment has gotten increased attention in the last few years, with different initiatives aiming to decrease transport emissions. While the EU has released a white paper stressing the need for modal shift towards rail transport, clear results remain absent. Therefore, this thesis explores improving the efficiency of the railway transport in the port area, specifically the port of Rotterdam. The goal is to both improve operational efficiency to decrease direct emissions, and incentivise modal shift towards railway transport.
To achieve these gains, an existing mathematical model is adapted to optimise the schedule for a single railway feeder services operator. A multi-objective function is minimised, to combine orders, reduce locomotive use and improve on time delivery. The model is benchmarked against a greedy algorithm, and structurally outperforms it.
Next, the feeder train services model (FTSM) is then used to investigate cooperative scheduling approaches. Cooperative game theory is used and the FTSM is run with stand-alone and pooled railway operators. For all scenarios tested, cooperating yields benefits, with cost reductions ranging from 25\% to 58\%, compared to stand-alone operation. The stable coalitions presented by this thesis present further gains in network capacity, as the pooled operators occupy less tracks.
This thesis fills the gap of port-specific railway freight transport, for which it both presents a novel mathematical model, and a cooperative strategy. The scenarios tested show benefits for all stakeholders, providing a solid base for further research and implementation.