Evolving the topology of subway networks using genetic algorithms

Existing public transportation networks are usually regarded as being static with respect to their topology. However, in fast growing cities, new lines are added, sometimes focusing only on the demand, without regard to overall efficiency of the system. In this work we propose the application of techniques from evolutionary computation. The aim here is to improve the efficiency of public transportation networks by altering the topology of links. We apply this approach to the particular case of the subway network of São Paulo, Brazil.