A Genetic Algorithm Based Railway Scheduling Model

In this paper we present an optimization model for train scheduling. This model constitutes one of the three major components of a solution approach for solving the transit network design problem. The problem of scheduling can be defined in the following general terms. Given the origin destination matrix for the train trips for design period, the underlying train network characterized by the overlapping routes. How optimally to allocate the trains among these routes? The train scheduling problem is solved in two levels. In the first level minimum frequency of trains required on each route. With the guarantee of load feasibility, is determined by considering each route individually. In the second level, the fleet size of first level is taken as upper bound and fleet size is again minimized by considering all routes together and using GAs. The model is applied to a real network, and results are presented.