An Improved Multi-objective Algorithm for the Urban Transit Routing Problem

The determination of efficient routes and schedules in public transport systems is complex due to the vast search space and multiple constraints involved. In this paper we focus on the Urban Transit Routing Problem concerned with the physical network design of public transport systems. Historically, route planners have used their local knowledge coupled with simple guidelines to produce network designs. Several major studies have identified the need for automated tools to aid in the design and evaluation of public transport networks. We propose a new construction heuristic used to seed a multi-objective evolutionary algorithm. Several problem specific mutation operators are then combined with an NSGAII framework leading to improvements upon previously published results.