Metaheuristic Method for Transport Modelling and Optimization
Public transport is a shared passenger transport service, which is available for use by general public. The operational efficiency of public transport is essential to provide good service. Therefore it needs to be optimized. The main public transport between cities, up to 1000 km, are trains and buses. It is important for transport operators to know how many peoples will use it. In this paper we propose a model of public transport. The problem is defined as multi-objective optimization problem. The two goals are minimum transportation time for all passengers and minimal price. We apply ant colony optimization approach to model the passenger flow. The model shows how many passengers will use a train and how many will use a bus according what is more important for them, the price or the time.
KeywordsTime Slot Public Transport Pareto Front Heuristic Information Passenger Flow
This work was partially supported by EC project AcomIn and by National Scientific fund by the grand I02/20.
- 2.Bonabeau, E., Dorigo, M., Theraulaz, G.: Swarm Intelligence: From Natural to Artificial Systems. Oxford University Press (1999)Google Scholar
- 3.Diaz-Parra, O., Ruiz-Vanoye, J.A., Loranca, B.B., Fuentes-Penna, A., Barrera-Camara, R.A.: A survey of transportation problems. J. Appl. Math. 2014, Article ID 848129, 17 pp (2014)Google Scholar
- 4.Dorigo, M., Stutzle, T.: Ant Colony Optimization. MIT Press (2004)Google Scholar
- 5.El Amaraoui, A., Mesghouni, K.: Train scheduling networks under time duration uncertainty. In: Proceedings of the 19th World Congress of the International Federation of Automatic Control, 2014, pp. 8762–8767 (2014)Google Scholar
- 6.Fidanova, S., Atanasov, K.: Generalized net model for the process of hybrid ant colony optimization. Comptes Randus de l’Academie Bulgare des Sciences 62(3), 315–322 (2009)Google Scholar
- 7.Hanseler, F.S., Molyneaux, N., Bierlaire, M., Stathopoulos, A.: Schedule-based estimation of pedestrian demand within a railway station. In: Proceedings of the Swiss Transportation Research Conference (STRC), 14–16 May 2014Google Scholar
- 8.Jin, J.G., Zhao, J., Lee, D.H.: A column generation based approach for the train network design optimization problem. J. Transp. Res. 50(1), 1–17 (2013)Google Scholar
- 10.Molyneaux, N., Hanseler, F., Bierlaire, M.: Modelling of train-induced pedestrian flows in railway stations. In: Proceedings of the Swiss Transportation Research Conference (STRC), 14–16 May 2014Google Scholar
- 11.Woroniuk, C., Marinov, M.: Simulation modelling to analyze the current level of utilization of sections along rail rout. J. Transport Lit. 7(2), 235–252 (2013)Google Scholar