Beta 1


Title "Improving bus timetables"
Author Guillaumet, Joan Ballano
Supervisor Rich, Jeppe (Traffic Modelling Group, Centre for Traffic and Transport, Technical University of Denmark, DTU, DK-2800 Kgs. Lyngby, Denmark)
Nielsen, Otto Anker (Traffic Modelling Group, Centre for Traffic and Transport, Technical University of Denmark, DTU, DK-2800 Kgs. Lyngby, Denmark)
Institution Technical University of Denmark, DTU, DK-2800 Kgs. Lyngby, Denmark
Thesis level Master's thesis
Year 2007
Abstract It is widely known the importance of the optimization of the cost of the public transport. This includes the time saving of the users as well as the real cost of the infrastructures. Literature shows that genetic algorithms are useful tool to reach the optimum in similar situations [ref. 01]. GA’s method creates a set of solutions, and in the same way as the real genetics, evolves solutions trough several generations until the optimum. This process makes the solution space explored much more extensive, thus becoming a good method for this problem. Applying GA’s to an existing single bus line, results showed that the behaviour of the GA converges to a minimum cost and the optimum timetable is similar to the existing one. These satisfactory results motivated the application of GA to a bus network. Although the optimal timetable obtained in this simulation does not bring relevant information since it is not based on a real network, the trend of the GA evolution is to converge in a minimum cost, in the same way as the optimization of a single bus line. In conclusion GA’s can be considered as a useful tool to optimize bus network scheduling problems. Nevertheless, further work in this subject using real networks and reliable data is encouraged so that more conclusive and realist results can be obtained.
Pages 94 s.
Fulltext
Original PDF Joan_Ballano_eksamensprojekt.pdf (1.27 MB)
Admin Creation date: 2007-07-06    Update date: 2007-07-06    Source: dtu    ID: 201609    Original MXD