Modelling and Solving a Train Path Assignment Model

Abstract

We introduce a binary linear model for solving the train path assignment problem. For each train request a train path has to be constructed from a set of predefined path parts within a time-space network. For each possible path we use a binary decision variable to indicate, whether the path is used by the train request. Track and halting capacity constraints are taken into account. We discuss different objective functions, like maximizing revenue or maximizing total train path quality. The problem is solved by using column generation within a branch and price approach. This paper gives some modeling and implementation details and presents computational results from real world instances.