Train timetable design under elastic passenger demand. (May 2018) - Robenek, Tomáš; Azadeh, Shadi Sharif; Maknoon, Yousef; de Lapparent, Matthieu; Bierlaire, Michel
Highlights: We replace the deterministic behavioral model of the passengers in the passenger centric train timetabling problem with a probabilistic one. We use a logit model, that has been calibrated to known demand elasticities, to predict the passenger behavior. We introduce a competing operator as an opt-out option for the passengers. We integrate the timetabling model with a pricing model. We maximize the operator's revenue by solving the Elastic Passenger Centric Train Timetabling Problem with pricing for different timetable designs using the Simulated Annealing heuristic. We use real network of Israeli Railways as our case study. The results show that the passenger behavior is having a significant impact on the operator's revenue. The knowledge of the passenger behavior allows for effective ticket pricing. Abstract: A passenger centric timetable is such a timetable that the satisfaction of the passengers is maximized. However, these timetables only maximize the probability of a passenger to take the train, but provide no insight on the actual choices of the passengers. Therefore, in this manuscript we replace the deterministic passenger satisfaction function with a probabilistic demand forecasting model inside of the passenger centric train timetable design. The actual forecasts lead to a realistic train occupation. Knowing the train occupation, we can estimate the revenue and to use pricing as a mobility management to further improve the level-of-service. We use a logit model that we calibrate to reflect the known demand elasticities. We further include a competing operator as an opt-out option for the passengers. Subsequently, we integrate the passenger centric train timetabling problem with a ticket pricing problem. We solve the elastic passenger centric train timetabling problem for various types of timetables using a simulated annealing heuristic on a case study of Israeli Railways. The results of our case study show that the generated revenues can be increased by up to 15% when taking into account the passengers' behavior along with a specific pricing scheme. This study further confirms the advantages of hybrid cyclicity.