A new methodology for the public transport network design

6Citations
Citations of this article
22Readers
Mendeley users who have this article in their library.
Get full text

Abstract

The present paper deals with the bus network design problem. Such problem is formulated as an optimization problem involving the minimization of all resources and costs related to the public transport system. The optimization problem is subject to user equilibrium on public transport network as well as to the bus capacity constraints and a set of feasibility constraints on route length and line frequency. The objective function is defined as the sum of operator's costs and users' costs. The input data are the public transport demand matrix, the characteristics of road network, the operating and users unit costs. Outputs are routes and frequencies for the lines of the public transport network. The performances of the network are estimated by a hyperpath transit assignment model, which reproduces the choice behaviour of transit users. The solving procedure consists of a set of heuristics, which includes a first routine for the definition of the roads and the zones to be served, a second step for the routes generation and then a genetic algorithm for finding a sub-optimal set of routes and associated frequencies. The GA is implemented in the C# language as a parallel genetic algorithm while the fitness evaluation requires computing, for each solution generated, the two terms of the objective function by simulating the public transport network with the EMME software. The proposed procedure will be implemented on a real large size network (two districts in the city of Rome), in order to compare its effectiveness with the performances of the existing transit network and to provide an extensive sensitivity analysis in bus frequency changes.

Cite

CITATION STYLE

APA

Ciaffi, F., Cipriani, E., Petrelli, M., & Ušpalytė-Vitkūnienė, R. (2014). A new methodology for the public transport network design. In 9th International Conference on Environmental Engineering, ICEE 2014. Dept. of Mathematical Modelling. https://doi.org/10.3846/enviro.2014.114

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free