Usually, when a rapid transit line is planned a less efficient system already partially covers the demand of the new line. Thus, when the rapid transit starts its regular services, the slow mode (e.g. bus lines) have to be cancelled or their routes modified. Usually this process is planned according to a sequential way. Firstly, the rapid transit line is designed taking into account private and public flows, and possibly surveys on mobility in order to predict the future utilization of the new infrastructure and/or other criteria. Then, in a second stage, the bus route network is redesigned. However, this sequential process can lead to a suboptimal solution, for which reason in this paper a cooperative model for rapid and slow transit network design is studied. The aim is to design simultaneously both networks and the objective is to maximize the number of passengers captured by both public modes against the private mode. We present a mathematical programming formulation and solve the problem by an improved Benders decomposition approach.

The railway planning problem consists of several consecutive phases: network design, line planning, timetabling, personnel assignment and rolling stocks planning. In this paper we will focus on the line planning process. Traditionally, the line planning problem consists of determining a set of lines and their frequencies optimizing a certain objective. In this work we will focus on the line planning problem context taking into account aspects related to rolling stock and crew operating costs. We assume that the number of possible vehicles is limited, that is, the problem that we are considering is a capacitated problem and the line network can be a crowding network. The main novelty in this paper is the consideration of the size of vehicles and frequencies as variables as well as the inclusion of a congestion function measuring the level of in-vehicle crowding. Concretely, we present the problem and an algorithm to solve it, which are tested via a computational experience.