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.

A Particle Swarm Optimization Algorithm for the Solution of the Transit Network Design Problem / Cipriani, Ernesto; Fusco, Gaetano; Maria Patella, Sergio; Petrelli, Marco. - In: SMART CITIES. - ISSN 2624-6511. - 3:2(2020), pp. 541-555. [10.3390/smartcities3020029]

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

GAETANO FUSCO
Supervision
;
2020

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.
2020
metaheuristics; bus transit network design; particle swarm optimization
01 Pubblicazione su rivista::01a Articolo in rivista
A Particle Swarm Optimization Algorithm for the Solution of the Transit Network Design Problem / Cipriani, Ernesto; Fusco, Gaetano; Maria Patella, Sergio; Petrelli, Marco. - In: SMART CITIES. - ISSN 2624-6511. - 3:2(2020), pp. 541-555. [10.3390/smartcities3020029]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1676717
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