A Particle Swarm Optimization Algorithm for the Solution of the Transit Network Design Problem

The research presented in this paper proposes a Particle Swarm Optimization (PSO) approach for solving the transit network design problem in large urban areas. The solving procedure is divided in two main phases: in the first step, a heuristic route generation algorithm provides a preliminary set of feasible and comparable routes, according to three dierent design criteria; in the second step, the optimal network configuration is found by applying a PSO-based procedure. This study presents a comparison between the results of the PSO approach and the results of a procedure based on Genetic Algorithms (GAs). Both methods were tested on a real-size network in Rome, in order to compare their eciency and eectiveness in optimal transit network calculation. The results show that the PSO approach promises more eciency and eectiveness than GAs in producing optimal solutions.