Waste Collection Vehicle Routing Problem Using Filling Predictions
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Haizea Rodriguez [1] ; Jon Díaz [1] ; Jenny Fajardo-Calderín [1] ; Asier Perallos [1] ; Enrique Onieva [1]
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[1] Universidad de Deusto
Universidad de Deusto
Bilbao, España
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- Localización: Hybrid Artificial Intelligent Systems: 16th International Conference, HAIS 2021. Bilbao, Spain. September 22–24, 2021. Proceedings / coord. por Hugo Sanjurjo González, Iker Pastor López
, Pablo García Bringas , Héctor Quintián Pardo , Emilio Santiago Corchado Rodríguez , 2021, ISBN 978-3-030-86271-8, págs. 637-648 - Idioma: inglés
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Resumen
With the increase in the global population and rising demand for food and other materials, there has been a rise in the amount of waste being generated daily by each house and locality. Most of the waste that is generated is thrown into the garbage containers, from where it is collected by the area municipalities. Improper management of waste in cities results in a huge loss to any smart city. However, with the importance that this has for the health of the citizens and the environment, there are few tools available to manage the planning of waste collection routes efficiently. In this paper, we present a solution to the planning of waste collection routes considering the existence of monitoring capabilities of the containers. The routing of the trucks for each of the days will be formulated as a Capacitated Vehicle Routing Problem. This research focuses on the minimization of the routing times, as well as avoiding the overflow probability. The paper presents the results of a case study with real data on three municipalities in the Basque Country, Spain.
