Train scheduling modeling and optimization on railways network

In this work, a mathematical formulation of the train scheduling problem is provided as a Mixed Integer Linear Program(MILP). Typically, the programs can be solved for easy cases, but computation time makes it impractical for more complex examples. Then a genetic algorithm is employed in the solution of the problem, with heuristic techniques to generate an initial population. The algorithm is applied to a number of problem instances producing feasible, though not optimal, solutions in less then one minute on a laptop computer. Some improvements are suggestedto obtain better results and further reduce the computation time.