Cobertura en servicios de Asistencia Vial
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Universidad Torcuato Di Tella
Abstract
El trabajo presenta una solución de asistencia vial en la Ciudad de Buenos Aires ensamblando
herramientas de optimización combinatoria y aprendizaje automático. El método dispone de
una red de estaciones estratégicamente seleccionadas para garantizar la cobertura del territorio
y luego estima la cantidad de móviles por estación en función de variables observadas durante
el período de un año. El resultado muestra mejoras cercanas al 35% en la tasa de auxilios
demorados, minimizando la cantidad de vehículos utilizados para la operación.
The work presents a road assistance solution in the City of Buenos Aires by assembling combinatorial optimization and machine learning tools. The method has a network of stations strategically selected to guarantee coverage of the territory and then estimates the number of units per station based on variables observed during a one-year period. The result shows improvements close to 35% in the delay rate, minimizing the number of vehicles used for the operation.
The work presents a road assistance solution in the City of Buenos Aires by assembling combinatorial optimization and machine learning tools. The method has a network of stations strategically selected to guarantee coverage of the territory and then estimates the number of units per station based on variables observed during a one-year period. The result shows improvements close to 35% in the delay rate, minimizing the number of vehicles used for the operation.
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Keywords
Seguridad del transporte, Seguridad vial