Work

A Particle Swarm Optimization Algorithm for the Solution of the Transit Network Design Problem

Year: 2020

Type: article

Abstract: The research presented in this paper proposes a Particle Swarm Optimization (PSO) approach for solving the transit network design problem in large urban areas. The solving procedure is divided in two main phases: in the first step, a heuristic route generation algorithm provides a preliminary set of feasible and comparable routes, according to three different design criteria; in the second step, the optimal network configuration is found by applying a PSO-based procedure. This study presents a comparison between the results of the PSO approach and the results of a procedure based on Genetic Algorithms (GAs). Both methods were tested on a real-size network in Rome, in order to compare their efficiency and effectiveness in optimal transit network calculation. The results show that the PSO approach promises more efficiency and effectiveness than GAs in producing optimal solutions.

Source: Smart Cities

DOI: 10.3390/smartcities3020029

Authors: Ernesto Cipriani, Gaetano Fusco, Sergio Maria Patella, Marco Petrelli

Institutions: Roma Tre University, Sapienza University of Rome, Mercatorum University

Language: English

Topic: Transportation Planning and Optimization

Subfield: Transportation

Field: Social Sciences

Domain: Social Sciences

SDGs: Industry, innovation and infrastructure, Sustainable cities and communities

Open Access status: gold

Estimated APC paid: $1,056