Scheduling of Electric Buses with Column Generation

Column generation has during the last years been popular in vehicle scheduling as it for larger problems can find an optimum faster than using an ordinary mixed-integer programming (MIP) model. We study the problem of finding optimal schedules for electric buses by means of column generation. The motive for this approach is that when the size of the problem becomes very large in terms of variables and different solutions, solving it with a mixed- integer programming model can take a lot time. The purpose of this work is to investigate how the best found integral solution and the solution time vary between different column generation methods and how these methods perform compared to a MIP. This has been done by implementing these methods on a test problem for scheduling of electric buses. The results indicate that column generation methods can be very efficient in terms of time and best found integral solution for larger problems. A modified column generation method has been created in order to accelerate the generation of columns, which is better than standard column generation in terms of solution time and best found integral solution.