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...

Descripción completa

Detalles Bibliográficos
Autores: Rodríguez Parra, Germán Ricardo, Guerrero, William Javier, Sarmiento-Lepesqueur, Angélica
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2017
País:Colombia
Institución:Universidad Nacional de Colombia
Repositorio:Repositorio UN
Idioma:español
OAI Identifier:oai:repositorio.unal.edu.co:unal/60374
Acceso en línea:https://repositorio.unal.edu.co/handle/unal/60374
http://bdigital.unal.edu.co/58706/
Access Level:acceso abierto
Palabra clave:62 Ingeniería y operaciones afines / Engineering
school bus routing
routing and scheduling
heuristics
traffic congestion
mathematical models
ruteo de buses escolares
ruteo y secuenciación
heurísticas
congestión vehicular, modelos matemáticos
Descripción
Sumario: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.