Modelos e Técnicas de Otimização de Estações de Recarga em Sistemas de Bicicletas Elétricas Compartilhadas: Um Mapeamento Sistemático
Resumo
A expansão dos sistemas de bicicletas elétricas compartilhadas impõe desafios à localização estratégica de estações de recarga, demandando integração entre dados operacionais, análise espacial e otimização. Este artigo apresenta um mapeamento sistemático, conduzido segundo o protocolo PRISMA 2020, para identificar modelos, critérios e técnicas computacionais aplicadas ao problema. Foram analisados 24 estudos (2013–2024), abrangendo MILP, heurísticas, GIS-MCDM e aprendizado de máquina. Como contribuição, evidenciando lacunas no uso de dados em tempo real e na modelagem sob incerteza.Referências
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BAHADORI, M.; et al. GIS-based multicriteria analysis for bike-sharing station location. Journal of Transport Geography, v. 96, 2022.
BASSOLAS, A.; et al. Spatiotemporal variability and prediction of e-bike battery levels in bike-sharing systems. Journal of Cleaner Production, 2024.
CHOWDHURY, S.; et al. Density-based clustering for urban mobility data. Applied Sciences, v. 13, n. 2, 2023.
CINTRANO, C.; CHICANO, F.; ALBA, E. Using metaheuristics for the location of bicycle stations. Applied Soft Computing, 2024.
COSTA LIMA, J.; et al. Big data integration of bike-sharing and bus systems in Fortaleza. Transport Policy, v. 132, 2023.
FRALEY, C.; RAFTERY, A. Model-based clustering, discriminant analysis, and density estimation. Journal of the American Statistical Association, v. 97, n. 458, p. 611–631, 2002.
GARCÍA-PALOMARES, J. C.; et al. GIS-based planning of bike-sharing systems. Transportation Research Part A, v. 49, 2012.
LAMONTAGNE, J.; et al. Optimising electric vehicle charging station placement using advanced discrete choice models. INFORMS Journal on Computing, v. 35, n. 5, p. 1195–1213, 2023.
LEI, T.; et al. Clustering approaches for bike-sharing demand. Journal of Transport Geography, v. 109, 2023.
NIKIFORIADIS, A.; et al. Hybrid approaches for bike-sharing optimization. Transportation Research Procedia, v. 47, 2020.
PAGE, M. J.; et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ, 2021.
STANĚK, R.; et al. Optimization models for bike-sharing station location. Transportation Research Part C, v. 149, 2023.
VON WAHL, A.; et al. Deep reinforcement learning for bike-sharing optimization. Transportation Research Part C, v. 143, 2022.
YU, H.; et al. Big data analytics for bike-sharing demand prediction. Transportation Research Part C, v. 128, 2021.
YUE, X.; et al. Deep reinforcement learning for e-scooter and bike-sharing optimization. Transportation Research Part C, v. 152, 2024.
ZHOU, Y.; et al. Predict-then-optimize approaches for bike-sharing. Sustainable Cities and Society, v. 85, 2022.
BAHADORI, M.; et al. GIS-based multicriteria analysis for bike-sharing station location. Journal of Transport Geography, v. 96, 2022.
BASSOLAS, A.; et al. Spatiotemporal variability and prediction of e-bike battery levels in bike-sharing systems. Journal of Cleaner Production, 2024.
CHOWDHURY, S.; et al. Density-based clustering for urban mobility data. Applied Sciences, v. 13, n. 2, 2023.
CINTRANO, C.; CHICANO, F.; ALBA, E. Using metaheuristics for the location of bicycle stations. Applied Soft Computing, 2024.
COSTA LIMA, J.; et al. Big data integration of bike-sharing and bus systems in Fortaleza. Transport Policy, v. 132, 2023.
FRALEY, C.; RAFTERY, A. Model-based clustering, discriminant analysis, and density estimation. Journal of the American Statistical Association, v. 97, n. 458, p. 611–631, 2002.
GARCÍA-PALOMARES, J. C.; et al. GIS-based planning of bike-sharing systems. Transportation Research Part A, v. 49, 2012.
LAMONTAGNE, J.; et al. Optimising electric vehicle charging station placement using advanced discrete choice models. INFORMS Journal on Computing, v. 35, n. 5, p. 1195–1213, 2023.
LEI, T.; et al. Clustering approaches for bike-sharing demand. Journal of Transport Geography, v. 109, 2023.
NIKIFORIADIS, A.; et al. Hybrid approaches for bike-sharing optimization. Transportation Research Procedia, v. 47, 2020.
PAGE, M. J.; et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ, 2021.
STANĚK, R.; et al. Optimization models for bike-sharing station location. Transportation Research Part C, v. 149, 2023.
VON WAHL, A.; et al. Deep reinforcement learning for bike-sharing optimization. Transportation Research Part C, v. 143, 2022.
YU, H.; et al. Big data analytics for bike-sharing demand prediction. Transportation Research Part C, v. 128, 2021.
YUE, X.; et al. Deep reinforcement learning for e-scooter and bike-sharing optimization. Transportation Research Part C, v. 152, 2024.
ZHOU, Y.; et al. Predict-then-optimize approaches for bike-sharing. Sustainable Cities and Society, v. 85, 2022.
Publicado
22/04/2026
Como Citar
ROCHA, Leonel da; ZAVADZKI, Leonardo S.; KOZIEVITCH, Nádia P..
Modelos e Técnicas de Otimização de Estações de Recarga em Sistemas de Bicicletas Elétricas Compartilhadas: Um Mapeamento Sistemático. In: ESCOLA REGIONAL DE BANCO DE DADOS (ERBD), 21. , 2026, Dois Vizinhos/PR.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2026
.
p. 39-48.
ISSN 2595-413X.
DOI: https://doi.org/10.5753/erbd.2026.20986.
