Diseño de una técnica de solución para el problema de enrutamiento de vehículos considerando factores ambientales

The Vehicle routing problem has been widely studied in the literature due to its impact on the operative decisions of any company that needs to deliver or pick-up merchandise. The current situation of the earth has led organizations to keep in mind the environmental factor in their operations. Therefore, it has been recently introduced to this area of study the green vehicle routing problem (GVRP), which aims to minimize the total amount of fuel consumed and CO2 generated by the fleet of vehicles. This thesis proposes several solution techniques to respond to the GVRP applied on a real-life scenario of a manufacturing company in Bogotá. For this purpose, an integer programming model and three different algorithms had been developed, namely, a heuristic, a tabú and a genetic algorithm. In order to measure the quality of the solutions different instances were made with three main variants: the number of clients, the number of vehicles, and the speed. The model, the heuristic, and the tabú algorithm were evaluated with and without time windows, the genetic algorithm was only considered for scenarios without time windows. The results obtained show that the genetic algorithm achives better values of the solution than the other desing methods, hence, this algorithm was applied to the real- life scenario. The solution method was able to reduce in 21,90% the total emission generated in comparison with the current operation.

• Autores: Arias Bula, Estefanía; Ávila Chaparro, Fernando; Jiménez Poveda, Carlos Santiago; Penagos Roberto, María Paula
• Tipo de recurso: Trabajo de grado de pregrado
• Fecha de publicación: 2019
• Institución: Pontificia Universidad Javeriana
• Repositorio: Repositorio Universidad Javeriana
• Idioma: spa
• OAI Identifier: oai:repository.javeriana.edu.co:10554/53110
• Acceso en línea: http://hdl.handle.net/10554/53110
• Palabra clave: Enrutamiento de vehículos; Emisiones de CO2; Ventanas de tiempo; Ingeniería industrial - Tesis y disertaciones académicas; Algoritmos (Computadores); Conservación del medio ambiente; Evaluación del impacto ambiental; Cambio climático
• Rights: openAccess
• License: Atribución-NoComercial-SinDerivadas 4.0 Internacional