This paper deals with the problem of planning an integrated transit system from the point of view of optimal fares and zone design. In other words, the matter is how to plan an integrated fare system that enables each passenger to travel within different zones with a single zone-based ticket. The main problem is very hard. Then, herewith it is proposed a two-level model, which is both quite near to real operation practices and makes the planner able to consider various transit firms operating within the same context. The main problem is divided into two distinct sub-problems: one for the fare problem, and the other for the zone problem, solved sequentially. The fare problem leads to the minimization of an aggregated cost function that is mainly related both to the budget needs of each transit agency, and changing in fare levels for the patronage. The zone problem is solved by a heuristic procedure, which has been set up in order to randomly search for the optimal zone configuration reflecting a given fare policy. Computational test results of the proposed model applied on a real database gathered in the metropolitan area of Florence (Italy) are also reported at the ending of this paper.
The combined zone and fare planning problem
PRATELLI, ANTONIO
2004-01-01
Abstract
This paper deals with the problem of planning an integrated transit system from the point of view of optimal fares and zone design. In other words, the matter is how to plan an integrated fare system that enables each passenger to travel within different zones with a single zone-based ticket. The main problem is very hard. Then, herewith it is proposed a two-level model, which is both quite near to real operation practices and makes the planner able to consider various transit firms operating within the same context. The main problem is divided into two distinct sub-problems: one for the fare problem, and the other for the zone problem, solved sequentially. The fare problem leads to the minimization of an aggregated cost function that is mainly related both to the budget needs of each transit agency, and changing in fare levels for the patronage. The zone problem is solved by a heuristic procedure, which has been set up in order to randomly search for the optimal zone configuration reflecting a given fare policy. Computational test results of the proposed model applied on a real database gathered in the metropolitan area of Florence (Italy) are also reported at the ending of this paper.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
