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

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Department of Engineering, Roma Tre University, Via Vito Volterra 62, 00146 Rome, Italy
2
Department of Civil, Construction and Environmental Engineering, Sapienza University of Rome, 00184 Rome, Italy
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Faculty of Economics, Universitas Mercatorum, Piazza Mattei, 10, 00186 Rome, Italy
*
Author to whom correspondence should be addressed.
Smart Cities 2020, 3(2), 541-555; https://doi.org/10.3390/smartcities3020029
Received: 22 March 2020 / Revised: 20 May 2020 / Accepted: 25 May 2020 / Published: 1 June 2020
(This article belongs to the Section Smart Transportation)
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. View Full-Text
Keywords: metaheuristics; bus transit network design; Particle Swarm Optimization. metaheuristics; bus transit network design; Particle Swarm Optimization.
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MDPI and ACS Style

Cipriani, E.; Fusco, G.; Patella, S.M.; Petrelli, M. A Particle Swarm Optimization Algorithm for the Solution of the Transit Network Design Problem. Smart Cities 2020, 3, 541-555. https://doi.org/10.3390/smartcities3020029

AMA Style

Cipriani E, Fusco G, Patella SM, Petrelli M. A Particle Swarm Optimization Algorithm for the Solution of the Transit Network Design Problem. Smart Cities. 2020; 3(2):541-555. https://doi.org/10.3390/smartcities3020029

Chicago/Turabian Style

Cipriani, Ernesto, Gaetano Fusco, Sergio M. Patella, and Marco Petrelli. 2020. "A Particle Swarm Optimization Algorithm for the Solution of the Transit Network Design Problem" Smart Cities 3, no. 2: 541-555. https://doi.org/10.3390/smartcities3020029

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