Cooperation strategies featuring optimization in the school transportation system in Bogota
The transport of students presents important challenges in the case of the city of Bogota, where an important cluster of schools is located in one zone, but there is only one road connecting these schools to residential zones. Thus, traffic congestion is high, generating long travel times for studen...
- Autores:
-
Rodríguez Parra, German Ricardo
Guerrero, William J.
Sarmiento Lepesqueur, Angélica
- Tipo de recurso:
- Article of investigation
- Fecha de publicación:
- 2017
- Institución:
- Escuela Colombiana de Ingeniería Julio Garavito
- Repositorio:
- Repositorio Institucional ECI
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.escuelaing.edu.co:001/1614
- Acceso en línea:
- https://repositorio.escuelaing.edu.co/handle/001/1614
http://dx.doi.org/10.15446/dyna.v84n202.65391
- Palabra clave:
- Transporte escolar - Bogotá
Estimación de tráfico vehicular - Bogotá
Flujo de tráfico - Bogotá
School transport - Bogota
Traffic estimation - Bogota
Traffic flow - Bogota
School bus routing
Routing and scheduling
Heuristics
Traffic congestion
Mathematical models
Ruteo de buses escolares
Ruteo y secuenciación
Heurísticas
Congestión vehicular
Modelos matemáticos
- Rights
- openAccess
- License
- https://creativecommons.org/licenses/by-nc-nd/4.0/
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| dc.title.eng.fl_str_mv |
Cooperation strategies featuring optimization in the school transportation system in Bogota |
| dc.title.alternative.spa.fl_str_mv |
Estrategias de cooperación en el sistema de transporte de estudiantes en Bogotá usando optimización |
| title |
Cooperation strategies featuring optimization in the school transportation system in Bogota |
| spellingShingle |
Cooperation strategies featuring optimization in the school transportation system in Bogota Transporte escolar - Bogotá Estimación de tráfico vehicular - Bogotá Flujo de tráfico - Bogotá School transport - Bogota Traffic estimation - Bogota Traffic flow - Bogota School bus routing Routing and scheduling Heuristics Traffic congestion Mathematical models Ruteo de buses escolares Ruteo y secuenciación Heurísticas Congestión vehicular Modelos matemáticos |
| title_short |
Cooperation strategies featuring optimization in the school transportation system in Bogota |
| title_full |
Cooperation strategies featuring optimization in the school transportation system in Bogota |
| title_fullStr |
Cooperation strategies featuring optimization in the school transportation system in Bogota |
| title_full_unstemmed |
Cooperation strategies featuring optimization in the school transportation system in Bogota |
| title_sort |
Cooperation strategies featuring optimization in the school transportation system in Bogota |
| dc.creator.fl_str_mv |
Rodríguez Parra, German Ricardo Guerrero, William J. Sarmiento Lepesqueur, Angélica |
| dc.contributor.author.none.fl_str_mv |
Rodríguez Parra, German Ricardo Guerrero, William J. Sarmiento Lepesqueur, Angélica |
| dc.subject.armarc.spa.fl_str_mv |
Transporte escolar - Bogotá Estimación de tráfico vehicular - Bogotá Flujo de tráfico - Bogotá |
| topic |
Transporte escolar - Bogotá Estimación de tráfico vehicular - Bogotá Flujo de tráfico - Bogotá School transport - Bogota Traffic estimation - Bogota Traffic flow - Bogota School bus routing Routing and scheduling Heuristics Traffic congestion Mathematical models Ruteo de buses escolares Ruteo y secuenciación Heurísticas Congestión vehicular Modelos matemáticos |
| dc.subject.armarc.eng.fl_str_mv |
School transport - Bogota Traffic estimation - Bogota Traffic flow - Bogota |
| dc.subject.proposal.eng.fl_str_mv |
School bus routing Routing and scheduling Heuristics Traffic congestion Mathematical models |
| dc.subject.proposal.spa.fl_str_mv |
Ruteo de buses escolares Ruteo y secuenciación Heurísticas Congestión vehicular Modelos matemáticos |
| description |
The transport of students presents important challenges in the case of the city of Bogota, where an important cluster of schools is located in one zone, but there is only one road connecting these schools to residential zones. Thus, traffic congestion is high, generating long travel times for students, high operational costs, and mobility problems. This paper studies the impacts of a cooperative strategy between logistics operators using a mixed integer programming mathematical model, to find the optimal design of school routes on a network with the topology that describes the aforementioned road system. Two strategies are compared: a mixed loads strategy, where students from different schools share buses; and a single load strategy, where students from different schools cannot share buses. The objective is to minimize the total operational costs while satisfying the schools’ time windows. Comparative results of the two models using exact and heuristic approaches are presented. |
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2017 |
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2017 |
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2021-07-01T17:40:13Z 2021-10-01T17:37:31Z |
| dc.date.available.none.fl_str_mv |
2021-07-01T17:40:13Z 2021-10-01T17:37:31Z |
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Artículo de revista |
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http://purl.org/coar/version/c_970fb48d4fbd8a85 |
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http://purl.org/coar/resource_type/c_2df8fbb1 |
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Text |
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10.15446/dyna.v84n202.65391 |
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http://dx.doi.org/10.15446/dyna.v84n202.65391 |
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Revista DYNA, 84(202), pp. 164-174, September, 2017. |
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Mollinedo, C. L., Movilidad Urbana Sostenible: Un reto para las ciudades del siglo XXI, Economía, Sociedad y Territorio, 6(22), pp. 1-35, 2006. Jaramillo-Molina, C., Ríos-Rivera, P.A. and Ortiz-Lasprilla, A.R., Incremento del parque automotor y su influencia en la congestión de las principales ciudades colombianas, Universidad del Valle, Cali, Colombia, 2009. Newton, R. and Thomas, W., Design of school bus routes by computer. Socio-Economic Planning Sciences, 3(1), pp. 75-85, 1969. DOI: 10.1016/0038-0121(69)90051-2 Park, J. and Kim, B.I., The school bus routing problem: A review. European Journal of Operational Research, 202(2), pp. 311-319, 2010. DOI: 10.1016/j.ejor.2009.05.017 Redacción Bogota, Este lunes arranca en firme carril exclusivo para rutas escolares en el norte de Bogota, EL ESPECTADOR, [en línea]. [Consultado: 16 de enero de 2017]. Disponible en: http://www.elespectador.com/noticias/bogota/lunes-arranca-firme-carril-exclusivo-rutas-escolares-el-articulo-674911. Lu, M., Sun, C. and Zheng, S., Congestion and pollution consequences of driving-to-school trips: A case study in beijing, Transportation Research, 50, pp. 280-291, 2016. DOI: 10.1016/j.trd.2016.10.023 Kelly, J.A. and Fu, M., Sustainable school commuting – Understanding choices and identifying opportunities: A case study in Dublin, Ireland, Journal of Transport Geography, 34, pp. 221-230, 2014. DOI: 10.1016/j.jtrangeo.2013.12.010 McDonald, N.C., Steiner, R.L., Palmer, W.M., Bullock, A.N., Sisiopiku, V.P. and Lytle, B.F., Costs of school transportation: Quantifying the fiscal impacts of encouraging walking and bicycling for school travel. Transportation, 43(1), pp. 159-175, 2016. DOI: 10.1007/s11116-014-9569-7 Bodin, L.B.L., Routing and scheduling of school buses by computer. Transportation Science, 13(2), pp. 113-129, 1979. DOI: 10.1287/trsc.13.2.113 Braca, J., Bramel, J., Posner,B. and Simchi-Levi., D., A computerized approach to the New York city school bus routing problem, IIE Transactions, 29, pp. 693-702, 1997. DOI: 10.1287/trsc.13.2.113 Montoya-Torres, J.R., López-Franco, J., Nieto-Isaza, S., Felizzola-Jiménez H .and Herazo-Padilla, N., A literature review on the vehicle routing problem with multiple depots, Computers & Industrial Engineering, 79, pp. 115-129, 2015. DOI: 10.1016/j.cie.2014.10.029 Liu, R., Jiang, Z. and Geng, N., A hybrid genetic algorithm for the multi-depot open vehicle routing problem, OR Spektrum, 36(2), pp. 401-421, 2014. DOI: 10.1007/s00291-013-0346-3 Lalla-Ruiz, E., Expósito-Izquierdo, C., Taheripour S. and Voß, S., An improved formulation for the multi-depot open vehicle routing problem, OR Spektrum, 38(1), pp. 1-13, 2015. DOI: 10.1007/s00291-015-0408-9 Schittekat, P., Kinable, J., Sörensen, K., Sevaux M. and Spieksma, F., A metaheuristic for the school bus routing problem with bus stop selection, European Journ al of Operational Research, (2), pp. 518-528, 2013. DOI: 10.1016/j.ejor.2013.02.025 Manumbu, D.M., Mujuni, E. and Kuznetsov, D., Mathematical formulation model for a school bus routing problem with small instance data, Mathematical Theory and Modeling, 4(8), pp. 121-132, 2014. Thangiah, S.R., Fergany, A., Wilson, B., Pitluga, A. and Mennell, W., School bus routing in rural school districts, Lecture Notes in Economics and Mathematical Systems, 600, pp. 209-232, 2008. DOI: 10.1007/978-3-540-73312-6_11 Euchi, J. and Mraihi, R., The urban bus routing problem in the Tunisian Case by the hybrid artificial ant colony algorithm, Swarm and Evolutionary Computation, 2, pp. 15-24, 2011. DOI: 10.1016/j.swevo.2011.10.002 Riera-Ledesma, J. and Salazar-González, J.J., Solving school bus routing using the multiple vehicle traveling purchaser problem: A branch-and-cut approach, Computers & Operations Research, 39(2), pp. 391-404, 2012. DOI: 10.1016/j.cor.2011.04.015 Zhang, J.J. and Li, Y.G., School bus problem and its algorithm, IERI Procedia, 2, pp. 8-11, 2012. DOI: 10.1016/j.ieri.2012.06.043 Arias-Rojas, J.S., Jiménez, J.F. and Montoya-Torres, J.R., Solving of school bus routing problem by ant colony optimization, Revista EIA, Escuela de Ingeniería de Antioquia, Medellín (Colombia), 17, pp. 193-208, 2012. Park, J., Tae, H. and Kim, B.I., A Post-improvement procedure for the mixed load school bus routing problem. European Journal of Operational Research, 217(1), pp. 204-213, 2012. DOI: 10.1016/j.ejor.2011.08.022 Ellegood, W.A., Campbell, J.F. and North, J., Continuous approximation models for mixed load school bus routing, Transportation Research, Part B(77), pp. 182-198, 2015. DOI: 10.1016/j.trb.2015.03.018 Yin, P.Y., Lyu S.R. and Chuang, Y.L., Cooperative coevolutionary approach for integrated vehicle routing and scheduling using cross-dock buffering. Engineering Applications of Artificial Intelligence, 52, pp. 40-53, 2016. DOI: 10.1016/j.engappai.2016.02.006 Vahdani, B. and Zandieh, M., Scheduling trucks in Cross-Docking systems: Robust meta-heuristics. Computers & Industrial Engineering, 58(1), pp. 12-24, 2010. DOI: 10.1016/j.cie.2009.06.006 Min, H., The multiple vehicle routing problem with simultaneous delivery and pick-up points, Transportation Research Part A: General, pp. 377-386, 1989. DOI: 10.1016/0191-2607(89)90085-X Sarmiento-Lepesqueur, A. y Quintero-Araujo, C.L., Estudio del problema de ruteo de vehículos con balance de carga: Aplicación de la meta-heurística Búsqueda Tabú, Tesis Maestría Gerencia de Operaciones, Universidad de la Sabana, Bogotá, Colombia, 2014. Guerrero, W.J., Velasco, N., Prodhon, C. and Amaya, C.A., On the generalized elementary shortest path problem: A heuristic approach. Electronic Notes in Discrete Mathematics, 41, pp. 503-510, 2013. DOI: 10.1016/j.endm.2013.05.131 |
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Rodríguez Parra, German Ricardo8e537539673d15b5514b98e1b868f263600Guerrero, William J.ed4b52885282a50f32a87ef1dff8e8b9600Sarmiento Lepesqueur, Angélica6bb238952f6233247dee4e4a1f93c2f36002021-07-01T17:40:13Z2021-10-01T17:37:31Z2021-07-01T17:40:13Z2021-10-01T17:37:31Z20170012-7353https://repositorio.escuelaing.edu.co/handle/001/161410.15446/dyna.v84n202.65391http://dx.doi.org/10.15446/dyna.v84n202.65391The transport of students presents important challenges in the case of the city of Bogota, where an important cluster of schools is located in one zone, but there is only one road connecting these schools to residential zones. Thus, traffic congestion is high, generating long travel times for students, high operational costs, and mobility problems. This paper studies the impacts of a cooperative strategy between logistics operators using a mixed integer programming mathematical model, to find the optimal design of school routes on a network with the topology that describes the aforementioned road system. Two strategies are compared: a mixed loads strategy, where students from different schools share buses; and a single load strategy, where students from different schools cannot share buses. The objective is to minimize the total operational costs while satisfying the schools’ time windows. Comparative results of the two models using exact and heuristic approaches are presented.El transporte de estudiantes tiene desafíos importantes en el caso de la ciudad de Bogotá, donde un grupo de escuelas se encuentra en una zona, pero sólo hay una carretera que las conecta con zonas residenciales. Por lo tanto, la congestión del tráfico es alta, generando largos tiempos de viaje, altos costos de operación y problemas de movilidad. Se estudia el impacto de una estrategia cooperativa entre operadores logísticos a través de modelos de programación de entera mixta, para encontrar el diseño óptimo de rutas escolares en una red con la topología que describe el mencionado sistema vial. Se comparan dos estrategias: Cargas mixtas y carga única, donde los estudiantes de diferentes escuelas comparten o no los autobuses disponibles. El objetivo es minimizar los costos totales de operación respetando las ventanas de tiempo de las escuelas. Se presentan los resultados comparativos de los modelos usando enfoques exactos y heurísticos.a Escuela Colombiana de Ingeniería Julio Garavito, Bogotá, Colombia. german.rodriguez-pa@mail.escuelaing.edu.co, angelica.sarmiento@escuelaing.edu.co b Facultad de Ingeniería, Universidad de la Sabana, Chía, Colombia. william.guerrero1@unisabana.edu.co11 páginasapplication/pdfengUniversidad Nacional de ColombiaBogotá, Colombia.https://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessAtribución-NoComercial-SinDerivadas 4.0 Internacional (CC BY-NC-ND 4.0)http://purl.org/coar/access_right/c_abf2https://revistas.unal.edu.co/index.php/dyna/article/view/65391Cooperation strategies featuring optimization in the school transportation system in BogotaEstrategias de cooperación en el sistema de transporte de estudiantes en Bogotá usando optimizaciónArtículo de revistainfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_2df8fbb1Textinfo:eu-repo/semantics/articlehttp://purl.org/redcol/resource_type/ARThttp://purl.org/coar/version/c_970fb48d4fbd8a85Revista DYNA, 84(202), pp. 164-174, September, 2017.17420216484N/ADYNAMollinedo, C. L., Movilidad Urbana Sostenible: Un reto para las ciudades del siglo XXI, Economía, Sociedad y Territorio, 6(22), pp. 1-35, 2006.Jaramillo-Molina, C., Ríos-Rivera, P.A. and Ortiz-Lasprilla, A.R., Incremento del parque automotor y su influencia en la congestión de las principales ciudades colombianas, Universidad del Valle, Cali, Colombia, 2009.Newton, R. and Thomas, W., Design of school bus routes by computer. Socio-Economic Planning Sciences, 3(1), pp. 75-85, 1969. DOI: 10.1016/0038-0121(69)90051-2Park, J. and Kim, B.I., The school bus routing problem: A review. European Journal of Operational Research, 202(2), pp. 311-319, 2010. DOI: 10.1016/j.ejor.2009.05.017Redacción Bogota, Este lunes arranca en firme carril exclusivo para rutas escolares en el norte de Bogota, EL ESPECTADOR, [en línea]. [Consultado: 16 de enero de 2017]. Disponible en: http://www.elespectador.com/noticias/bogota/lunes-arranca-firme-carril-exclusivo-rutas-escolares-el-articulo-674911.Lu, M., Sun, C. and Zheng, S., Congestion and pollution consequences of driving-to-school trips: A case study in beijing, Transportation Research, 50, pp. 280-291, 2016. DOI: 10.1016/j.trd.2016.10.023Kelly, J.A. and Fu, M., Sustainable school commuting – Understanding choices and identifying opportunities: A case study in Dublin, Ireland, Journal of Transport Geography, 34, pp. 221-230, 2014. DOI: 10.1016/j.jtrangeo.2013.12.010McDonald, N.C., Steiner, R.L., Palmer, W.M., Bullock, A.N., Sisiopiku, V.P. and Lytle, B.F., Costs of school transportation: Quantifying the fiscal impacts of encouraging walking and bicycling for school travel. Transportation, 43(1), pp. 159-175, 2016. DOI: 10.1007/s11116-014-9569-7Bodin, L.B.L., Routing and scheduling of school buses by computer. Transportation Science, 13(2), pp. 113-129, 1979. DOI: 10.1287/trsc.13.2.113Braca, J., Bramel, J., Posner,B. and Simchi-Levi., D., A computerized approach to the New York city school bus routing problem, IIE Transactions, 29, pp. 693-702, 1997. DOI: 10.1287/trsc.13.2.113Montoya-Torres, J.R., López-Franco, J., Nieto-Isaza, S., Felizzola-Jiménez H .and Herazo-Padilla, N., A literature review on the vehicle routing problem with multiple depots, Computers & Industrial Engineering, 79, pp. 115-129, 2015. DOI: 10.1016/j.cie.2014.10.029Liu, R., Jiang, Z. and Geng, N., A hybrid genetic algorithm for the multi-depot open vehicle routing problem, OR Spektrum, 36(2), pp. 401-421, 2014. DOI: 10.1007/s00291-013-0346-3Lalla-Ruiz, E., Expósito-Izquierdo, C., Taheripour S. and Voß, S., An improved formulation for the multi-depot open vehicle routing problem, OR Spektrum, 38(1), pp. 1-13, 2015. DOI: 10.1007/s00291-015-0408-9Schittekat, P., Kinable, J., Sörensen, K., Sevaux M. and Spieksma, F., A metaheuristic for the school bus routing problem with bus stop selection, European Journ al of Operational Research, (2), pp. 518-528, 2013. DOI: 10.1016/j.ejor.2013.02.025Manumbu, D.M., Mujuni, E. and Kuznetsov, D., Mathematical formulation model for a school bus routing problem with small instance data, Mathematical Theory and Modeling, 4(8), pp. 121-132, 2014.Thangiah, S.R., Fergany, A., Wilson, B., Pitluga, A. and Mennell, W., School bus routing in rural school districts, Lecture Notes in Economics and Mathematical Systems, 600, pp. 209-232, 2008. DOI: 10.1007/978-3-540-73312-6_11Euchi, J. and Mraihi, R., The urban bus routing problem in the Tunisian Case by the hybrid artificial ant colony algorithm, Swarm and Evolutionary Computation, 2, pp. 15-24, 2011. DOI: 10.1016/j.swevo.2011.10.002Riera-Ledesma, J. and Salazar-González, J.J., Solving school bus routing using the multiple vehicle traveling purchaser problem: A branch-and-cut approach, Computers & Operations Research, 39(2), pp. 391-404, 2012. DOI: 10.1016/j.cor.2011.04.015Zhang, J.J. and Li, Y.G., School bus problem and its algorithm, IERI Procedia, 2, pp. 8-11, 2012. DOI: 10.1016/j.ieri.2012.06.043Arias-Rojas, J.S., Jiménez, J.F. and Montoya-Torres, J.R., Solving of school bus routing problem by ant colony optimization, Revista EIA, Escuela de Ingeniería de Antioquia, Medellín (Colombia), 17, pp. 193-208, 2012.Park, J., Tae, H. and Kim, B.I., A Post-improvement procedure for the mixed load school bus routing problem. European Journal of Operational Research, 217(1), pp. 204-213, 2012. DOI: 10.1016/j.ejor.2011.08.022Ellegood, W.A., Campbell, J.F. and North, J., Continuous approximation models for mixed load school bus routing, Transportation Research, Part B(77), pp. 182-198, 2015. DOI: 10.1016/j.trb.2015.03.018Yin, P.Y., Lyu S.R. and Chuang, Y.L., Cooperative coevolutionary approach for integrated vehicle routing and scheduling using cross-dock buffering. Engineering Applications of Artificial Intelligence, 52, pp. 40-53, 2016. DOI: 10.1016/j.engappai.2016.02.006Vahdani, B. and Zandieh, M., Scheduling trucks in Cross-Docking systems: Robust meta-heuristics. Computers & Industrial Engineering, 58(1), pp. 12-24, 2010. DOI: 10.1016/j.cie.2009.06.006Min, H., The multiple vehicle routing problem with simultaneous delivery and pick-up points, Transportation Research Part A: General, pp. 377-386, 1989. 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DOI: 10.1016/j.endm.2013.05.131Transporte escolar - BogotáEstimación de tráfico vehicular - BogotáFlujo de tráfico - BogotáSchool transport - BogotaTraffic estimation - BogotaTraffic flow - BogotaSchool bus routingRouting and schedulingHeuristicsTraffic congestionMathematical modelsRuteo de buses escolaresRuteo y secuenciaciónHeurísticasCongestión vehicularModelos matemáticosTEXT10.15446/dyna.v84n202.65391.pdf.txt10.15446/dyna.v84n202.65391.pdf.txtExtracted texttext/plain58921https://repositorio.escuelaing.edu.co/bitstream/001/1614/3/10.15446/dyna.v84n202.65391.pdf.txt41a66988a521081af5306be1d335439dMD53open accessCooperation strategies featuring optimization in the school transportation system in Bogota.pdf.txtCooperation strategies featuring optimization in the school transportation system in Bogota.pdf.txtExtracted texttext/plain58921https://repositorio.escuelaing.edu.co/bitstream/001/1614/5/Cooperation%20strategies%20featuring%20optimization%20in%20the%20school%20transportation%20system%20in%20Bogota.pdf.txt41a66988a521081af5306be1d335439dMD55open accessTHUMBNAIL10.15446/dyna.v84n202.65391.pdf.jpg10.15446/dyna.v84n202.65391.pdf.jpgGenerated Thumbnailimage/jpeg16159https://repositorio.escuelaing.edu.co/bitstream/001/1614/4/10.15446/dyna.v84n202.65391.pdf.jpgb15b7719f1d5d0319d211e874291917fMD54open accessCooperation strategies featuring optimization in the school transportation system in Bogota.pdf.jpgCooperation strategies featuring optimization in the school transportation system in Bogota.pdf.jpgGenerated Thumbnailimage/jpeg16159https://repositorio.escuelaing.edu.co/bitstream/001/1614/6/Cooperation%20strategies%20featuring%20optimization%20in%20the%20school%20transportation%20system%20in%20Bogota.pdf.jpgb15b7719f1d5d0319d211e874291917fMD56open accessLICENSElicense.txttext/plain1881https://repositorio.escuelaing.edu.co/bitstream/001/1614/1/license.txt5a7ca94c2e5326ee169f979d71d0f06eMD51open accessORIGINALCooperation strategies featuring optimization in the school transportation system in Bogota.pdfapplication/pdf764785https://repositorio.escuelaing.edu.co/bitstream/001/1614/2/Cooperation%20strategies%20featuring%20optimization%20in%20the%20school%20transportation%20system%20in%20Bogota.pdfcaa6e5c7e4f5bef52503b44e8c54da15MD52open access001/1614oai:repositorio.escuelaing.edu.co:001/16142022-09-04 03:00:56.222open accessRepositorio Escuela Colombiana de Ingeniería Julio Garavitorepositorio.eci@escuelaing.edu.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 |