Trains in Symbiosis Optimising Train Schedules with Symbiotic Networks

K. Pieters (The Netherlands)


Artificial Intelligence, optimisation, pneulian reactive systems, network.


Train Scheduling is extremely difficult in a dense railway infrastructure such as that of the Netherlands. Trains travelling at periodic time intervals, with different speed and trajectories, share the same infrastructure, which introduces the risk of conflicts and therefore loss of efficiency. Such conflicts are a function of the departure times of the various trains and therefore there should be a set of departure times which minimises the impediments. This paper is a record of a research that investigated the ability of symbiotic networks to find such a set of departure times. The theory of symbiotic networks has been used to optimise a simulation of the Dutch railway system as an exercise in applying such a network to solve practical problems. This paper records the experiments that have been carried out, and their results.

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