91B74 Models of real-world systems
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Keywords
- demand function (2)
- fare planning (2)
- descrete choice (1)
- discrete choice model (1)
- fares (1)
- macroscopic railway modeling (1)
- network aggregation (1)
- optimization (1)
- public transport (1)
Application Area
- B (4)
In this paper a bottom-up approach of automatic simplification of a railway network is presented. Starting from a very detailed, microscopic level, as it is used in railway simulation, the network is transformed by an algorithm to a less detailed level (macroscopic network), that is sufficient for long-term planning and optimization. In addition running and headway times are rounded to a pre-chosen time discretization by a special cumulative method, which we will present and analyse in this paper. After the transformation we fill the network with given train requests to compute an optimal slot allocation. Then the optimized schedule is re-transformed into the microscopic level and can be simulated without any conflicts occuring between the slots. The algorithm is used to transform the network of the very dense Simplon corridor between Swiss and Italy. With our aggregation it is possible for the first time to generate a profit maximal and conflict free timetable for the corridor across a day by a simultaneously optimization run.
The optimization of fare systems in public transit allows to pursue
objectives such as the maximization of demand, revenue, profit, or
social welfare. We propose a non-linear optimization approach to fare
planning that is based on a detailed discrete choice model of user
behavior. The approach allows to analyze different fare structures,
optimization objectives, and operational scenarios involving, e.g.,
subsidies. We use the resulting models to compute optimized fare
systems for the city of Potsdam, Germany.
In this paper we investigate the fare planning model for public
transport, which consists in designing a system of fares maximizing
the revenue. We discuss a discrete choice model in which passengers
choose between different travel alternatives to express the demand as
a function of fares. Furthermore, we give a computational example for
the city of Potsdam and discuss some theoretical aspects.
Die Angebotsplanung im öffentlichen Nahverkehr umfasst die Aufgaben der Netz-, Linien-,
Fahr- und Preisplanung. Wir stellen zwei mathematische Optimierungsmodelle zur Linien- und
Preisplanung vor. Wir zeigen anhand von Berechnungen für die Verkehrsbetriebe in Potsdam
(ViP), dass sich damit komplexe Zusammenhänge quantitativ analysieren lassen. Auf diese
Weise untersuchen wir die Auswirkungen von Freiheitsgraden auf die Konstruktion von Linien
und die Wahl von Reisewegen der Passagiere, Abhängigkeiten zwischen Kosten und Reisezeiten
sowie den Einfluss verschiedener Preissysteme auf Nachfrage und Kostendeckung.
The fare planning problem for public transport is to design a system of fares that maximize the revenue. We introduce a nonlinear optimization model to approach this problem. It is based on a discrete choice logit model that expresses demand as a function of the fares. We illustrate our approach by computing and comparing two different fare systems for the intercity network of the Netherlands.