Mathematical model for assigning an optimal frequency of buses in an integrated transport system

This paper proposes a mathematical model to estimate the frequency setting of the buses for a specific route on any given hour in public transportation systems. This model can be used for three different purposes: determine how many buses a route needs to fully satisfy its demand, estimate an optima...

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Autores:
Tipo de recurso:
Fecha de publicación:
2018
Institución:
Universidad Tecnológica de Bolívar
Repositorio:
Repositorio Institucional UTB
Idioma:
eng
OAI Identifier:
oai:repositorio.utb.edu.co:20.500.12585/8908
Acceso en línea:
https://hdl.handle.net/20.500.12585/8908
Palabra clave:
Frequency setting
Mathematical model
Public transportation
Transportation
Waiting time
Buses
Estimation
Heuristic methods
Mathematical models
Optimization
Transportation
Transportation routes
Travel time
Bus frequency
Frequency setting
Integrated transport
Optimal frequency
Public transportation
Public transportation systems
Use-case
Waiting-time
Bus transportation
Rights
restrictedAccess
License
http://creativecommons.org/licenses/by-nc-nd/4.0/
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oai_identifier_str oai:repositorio.utb.edu.co:20.500.12585/8908
network_acronym_str UTB2
network_name_str Repositorio Institucional UTB
repository_id_str
dc.title.none.fl_str_mv Mathematical model for assigning an optimal frequency of buses in an integrated transport system
title Mathematical model for assigning an optimal frequency of buses in an integrated transport system
spellingShingle Mathematical model for assigning an optimal frequency of buses in an integrated transport system
Frequency setting
Mathematical model
Public transportation
Transportation
Waiting time
Buses
Estimation
Heuristic methods
Mathematical models
Optimization
Transportation
Transportation routes
Travel time
Bus frequency
Frequency setting
Integrated transport
Optimal frequency
Public transportation
Public transportation systems
Use-case
Waiting-time
Bus transportation
title_short Mathematical model for assigning an optimal frequency of buses in an integrated transport system
title_full Mathematical model for assigning an optimal frequency of buses in an integrated transport system
title_fullStr Mathematical model for assigning an optimal frequency of buses in an integrated transport system
title_full_unstemmed Mathematical model for assigning an optimal frequency of buses in an integrated transport system
title_sort Mathematical model for assigning an optimal frequency of buses in an integrated transport system
dc.contributor.editor.none.fl_str_mv Serrano C. J.E.
Martínez-Santos, Juan Carlos
dc.subject.keywords.none.fl_str_mv Frequency setting
Mathematical model
Public transportation
Transportation
Waiting time
Buses
Estimation
Heuristic methods
Mathematical models
Optimization
Transportation
Transportation routes
Travel time
Bus frequency
Frequency setting
Integrated transport
Optimal frequency
Public transportation
Public transportation systems
Use-case
Waiting-time
Bus transportation
topic Frequency setting
Mathematical model
Public transportation
Transportation
Waiting time
Buses
Estimation
Heuristic methods
Mathematical models
Optimization
Transportation
Transportation routes
Travel time
Bus frequency
Frequency setting
Integrated transport
Optimal frequency
Public transportation
Public transportation systems
Use-case
Waiting-time
Bus transportation
description This paper proposes a mathematical model to estimate the frequency setting of the buses for a specific route on any given hour in public transportation systems. This model can be used for three different purposes: determine how many buses a route needs to fully satisfy its demand, estimate an optimal bus frequency to satisfy the maximum amount of demand when the number of buses is fixed and estimate an optimal bus frequency to satisfy a given percentage of demand. It receives three entries: number of buses assigned to the route, which can vary or not depends on its purpose, the travel time for the route and the route’s demand. A series of equations are proposed using a heuristic method, which allows calculating the frequency of a route at any given hour of the day. A use case experiment is applied to help understand how to use the model on it’s different suggested uses. Additionally, exposes how the proposed model could improve an actual one. The results of this experiment case showed that the demand could be fulfilled using one of this model’s cases. © Springer Nature Switzerland AG 2018.
publishDate 2018
dc.date.issued.none.fl_str_mv 2018
dc.date.accessioned.none.fl_str_mv 2020-03-26T16:32:35Z
dc.date.available.none.fl_str_mv 2020-03-26T16:32:35Z
dc.type.coarversion.fl_str_mv http://purl.org/coar/version/c_970fb48d4fbd8a85
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dc.type.hasversion.none.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.spa.none.fl_str_mv Conferencia
status_str publishedVersion
dc.identifier.citation.none.fl_str_mv Communications in Computer and Information Science; Vol. 885, pp. 70-82
dc.identifier.isbn.none.fl_str_mv 9783319989976
dc.identifier.issn.none.fl_str_mv 18650929
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/20.500.12585/8908
dc.identifier.doi.none.fl_str_mv 10.1007/978-3-319-98998-3_6
dc.identifier.instname.none.fl_str_mv Universidad Tecnológica de Bolívar
dc.identifier.reponame.none.fl_str_mv Repositorio UTB
dc.identifier.orcid.none.fl_str_mv 57204067041
26325154200
identifier_str_mv Communications in Computer and Information Science; Vol. 885, pp. 70-82
9783319989976
18650929
10.1007/978-3-319-98998-3_6
Universidad Tecnológica de Bolívar
Repositorio UTB
57204067041
26325154200
url https://hdl.handle.net/20.500.12585/8908
dc.language.iso.none.fl_str_mv eng
language eng
dc.relation.conferencedate.none.fl_str_mv 26 September 2018 through 28 September 2018
dc.rights.coar.fl_str_mv http://purl.org/coar/access_right/c_16ec
dc.rights.uri.none.fl_str_mv http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rights.accessrights.none.fl_str_mv info:eu-repo/semantics/restrictedAccess
dc.rights.cc.none.fl_str_mv Atribución-NoComercial 4.0 Internacional
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-nd/4.0/
Atribución-NoComercial 4.0 Internacional
http://purl.org/coar/access_right/c_16ec
eu_rights_str_mv restrictedAccess
dc.format.medium.none.fl_str_mv Recurso electrónico
dc.format.mimetype.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Springer Verlag
publisher.none.fl_str_mv Springer Verlag
dc.source.none.fl_str_mv https://www.scopus.com/inward/record.uri?eid=2-s2.0-85054370898&doi=10.1007%2f978-3-319-98998-3_6&partnerID=40&md5=05701195cd4ba947890a5c65705e2450
institution Universidad Tecnológica de Bolívar
dc.source.event.none.fl_str_mv 13th Colombian Conference on Computing, CCC 2018
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spelling Serrano C. J.E.Martínez-Santos, Juan CarlosQuintero J.S.M.Martínez Santos J.C.2020-03-26T16:32:35Z2020-03-26T16:32:35Z2018Communications in Computer and Information Science; Vol. 885, pp. 70-82978331998997618650929https://hdl.handle.net/20.500.12585/890810.1007/978-3-319-98998-3_6Universidad Tecnológica de BolívarRepositorio UTB5720406704126325154200This paper proposes a mathematical model to estimate the frequency setting of the buses for a specific route on any given hour in public transportation systems. This model can be used for three different purposes: determine how many buses a route needs to fully satisfy its demand, estimate an optimal bus frequency to satisfy the maximum amount of demand when the number of buses is fixed and estimate an optimal bus frequency to satisfy a given percentage of demand. It receives three entries: number of buses assigned to the route, which can vary or not depends on its purpose, the travel time for the route and the route’s demand. A series of equations are proposed using a heuristic method, which allows calculating the frequency of a route at any given hour of the day. A use case experiment is applied to help understand how to use the model on it’s different suggested uses. Additionally, exposes how the proposed model could improve an actual one. The results of this experiment case showed that the demand could be fulfilled using one of this model’s cases. © Springer Nature Switzerland AG 2018.Recurso electrónicoapplication/pdfengSpringer Verlaghttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/restrictedAccessAtribución-NoComercial 4.0 Internacionalhttp://purl.org/coar/access_right/c_16echttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85054370898&doi=10.1007%2f978-3-319-98998-3_6&partnerID=40&md5=05701195cd4ba947890a5c65705e245013th Colombian Conference on Computing, CCC 2018Mathematical model for assigning an optimal frequency of buses in an integrated transport systeminfo:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionConferenciahttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_c94fFrequency settingMathematical modelPublic transportationTransportationWaiting timeBusesEstimationHeuristic methodsMathematical modelsOptimizationTransportationTransportation routesTravel timeBus frequencyFrequency settingIntegrated transportOptimal frequencyPublic transportationPublic transportation systemsUse-caseWaiting-timeBus transportation26 September 2018 through 28 September 2018Ceder, A., Wilson, N.H.M., Bus network design (1986) Transp. Res. Part B: Methodol., 20 (4), pp. 331-344Chriqui, C., Robillard, P., Common bus lines (1975) Transp. Sci., 9 (2), pp. 115-121Han, A.F., Wilson, N.H.M., The allocation of buses in heavily utilized networks with overlapping routes (1982) Transp. Res. Part B: Methodol., 16 (3), pp. 221-232Huang, Z., Ren, G., Liu, H., Optimizing bus frequencies under uncertain demand: Case study of the transit network in a developing city (2013) Math. Probl. Eng., 10 (2013)John, M.P., (2016) Metaheuristics for Designing Efficient Routes & Schedules for Urban Transportation Networks, , Ph.D. thesis, Cardiff UniversityMueller, N., Urban and transport planning related exposures and mortality: A health impact assessment for cities (2017) Environ. Health Perspect., 125 (1), p. 89Parbo, J., Nielsen, O.A., Prato, C.G., User perspectives in public transport timetable optimisation (2014) Transp. Res. Part C: Emerg. Technol., 48, pp. 269-284Rasmussen, T.K., Anderson, M.K., Nielsen, O.A., Prato, C.G., Timetable-based simulation method for choice set generation in large-scale public transport networks (2016) Eur. J. Transp. Infrastruct. Res., 16 (3), pp. 467-489Schéele, S., A supply model for public transit services (1980) Transp. Res. Part B: Methodol., 14 (1), pp. 133-146Song, B., Wynter, L., (2017) Real-Time Public Transport Service-Level Monitoring Using Passive WIFI: A Spectral Clustering Approach for Train Timetable EstimationWagale, M., Singh, A.P., Sarkar, A.K., Arkatkar, S., Real-time optimal bus scheduling for a city using a DTR model (2013) Procedia-Soc. Behav. Sci., 104, pp. 845-854http://purl.org/coar/resource_type/c_c94fTHUMBNAILMiniProdInv.pngMiniProdInv.pngimage/png23941https://repositorio.utb.edu.co/bitstream/20.500.12585/8908/1/MiniProdInv.png0cb0f101a8d16897fb46fc914d3d7043MD5120.500.12585/8908oai:repositorio.utb.edu.co:20.500.12585/89082023-05-26 16:30:20.297Repositorio Institucional UTBrepositorioutb@utb.edu.co