Automated train scheduling system using Genetic Algorithm

The increment of interest for transport service in rail activity stipulates higher proportion of consumed infrastructure capacity. In this system of activity stream, even minor deviations from the arranged schedule can affect its stability, and this can bring about a noteworthy diminishment of the nature of transport service. Given the way that the railroad business is as of now running without much abundance limit, better arranging and planning instruments are expected to successfully deal with the rare assets, keeping in mind the ultimate goal to adapt to the quickly expanding interest for rail route transportation. The objective of operational scheduling of trains is to safely move about each train, as fast as possible, from its origin to its destination such that the total delay of all trains can be minimized. This paper presents a (Fixed Path + Genetic Algorithm) heuristic model, an optimization-based approach for scheduling of trains. The Fixed Path model assumes that path of the trains is fixed for preparing the train schedule. The Genetic Algorithm is used for selecting the path for each train that takes minimum time to arrive at the destination. Together it presents a schedule that can minimize the travel time of each train maximizing capacity of the network. This paper proves the fact that applying the proposed model, rail traffic can be improved regarding the increase of the timetable stability and maximizing capacity subject to safety constraints.