Abstract
Increasing complexity in municipal solid waste streams worldwide is pressing Solid Waste Management Systems (SWMS), which need solutions to manage the waste properly. Waste collection and transport is the first task, traditionally carried out by countries/municipalities responsible for waste management. In this approach, drivers are responsible for decision-making regarding collection routes, leading to inefficient resource expenses. In this sense, strategies to optimize waste collection routes are receiving increasing interest from authorities, companies and the scientific community. Works in this strand usually focus on waste collection route optimization in big cities, but small towns could also benefit from technological development to improve their SWMS. Waste collection is related to combinatorial optimization that can be modeled as the capacitated vehicle routing problem. In this paper, a Capacitated Waste Collection Problem will be considered to evaluate the performance of metaheuristic approaches in waste collection optimization in the city of Bragança, Portugal. The algorithms used are available on Google OR-tools, an open-source tool with modules for solving routing problems. The Guided Local Search obtained the best results in optimizing waste collection planning. Furthermore, a comparison with real waste collection data showed that the results obtained with the application of OR-Tools are promising to save resources in waste collection.
This work has been supported by FCT - Fundação para a Ciência e Tecnologia within the R &D Units Project Scope: UIDB/05757/2020, UIDB/00690/2020, UIDB/50 020/2020, and UIDB/00319/2020. Adriano Silva was supported by FCT-MIT Portugal PhD grant SFRH/BD/151346/2021, and Filipe Alves was supported by FCT PhD grant SFRH/BD/143745/2019.
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Silva, A.S. et al. (2022). Solving a Capacitated Waste Collection Problem Using an Open-Source Tool. In: Gervasi, O., Murgante, B., Misra, S., Rocha, A.M.A.C., Garau, C. (eds) Computational Science and Its Applications – ICCSA 2022 Workshops. ICCSA 2022. Lecture Notes in Computer Science, vol 13378. Springer, Cham. https://doi.org/10.1007/978-3-031-10562-3_11
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