RT journal article
T1 A novel multi-objective optimization approach to guarantee quality of service and energy efficiency in a heterogeneous bus fleet system
A1 Peña, David
A1 Tchernykh, Andrei
A1 Dorronsoro Díaz, Bernabé
A1 Ruiz Villalobos, Patricia
A2 Ingeniería Informática
A2 Ingeniería Mecánica y Diseño Industrial
K1 Public transport
K1 sustainable cities
K1 greenhouse gas emission
K1 multi-objective optimization
K1 evolutionary algorithms
AB An efficient public transport system is essential for sustainable city development, as it directly affects people’s welfare. This article addresses the urban public transport timetabling problem with multi-objective evolutionary algorithms, considering multiple vehicle types and respecting the public transport restrictions of local authorities. The conflicting objectives are the minimization of fuel consumption and unsatisfied user demand, which are essential to make transit buses an attractive alternative for users, thus promoting environmentally friendly mobility. The problem was solved with two well-known metaheuristics, namely the non-dominated sorting genetic algorithm-II (NSGA-II) and cellular genetic algorithm for multi-objective optimization (MOCell), and their performance was compared using several metrics. Their parameters were tuned with a thorough study, and several evolutionary operators designed for the problem were considered. The outcomes suggest that a solution using various types of buses can produce diverse dispatching strategies, reducing pollutant emissions and maintaining tolerable ridership losses.
PB Taylor & Francis
SN 1029-0273
YR 2023
FD 2023
LK http://hdl.handle.net/10498/35436
UL http://hdl.handle.net/10498/35436
LA eng
NO This project was partially funded by the Spanish Ministerio de Ciencia, Innovación y Universidades and the ERDF [contract RTI2018-100754-B-I00] (iSUN project), ERDF [project FEDER-UCA18-108393] (OPTIMALE), and Junta de Andalucía and ERDF (GENIUS) [project P18-2399].
DS Repositorio Institucional de la Universidad de Cádiz
RD 22-sep-2026