Skip to main content
Springer Nature Link
Log in

Optimizing Waste Collection in Constrained Urban Spaces: A Hybrid Fleet Approach

  • Conference paper
  • First Online:
Optimization, Learning Algorithms and Applications (OL2A 2024)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 2281))

  • 135 Accesses

Abstract

The automotive industry is witnessing a surge in the production of electric vehicles (EVs) driven by stringent emission regulations. Despite this growth, heavy-duty truck fleets, particularly in waste collection, remain predominantly combustion-based ones. Waste collection is critical in urban environments, presenting unique challenges due to confined operational regions. One alternative to increase EVs in waste collection is to substitute the smaller truck fleets used for waste collection in constrained environments, such as narrow streets, by EVs. In this paper, we present a new formulation for the waste collection problem that considers a truck fleet comprised of smaller EVs and regular combustion trucks. The smaller trucks are proposed for the waste collection of specific sites (i.e. dumpsters in narrow streets). Our formulation considers battery limitations of electric trucks and flexible time windows for the waste collection task. The solution was validated by comparing the emission of CO2 and collection costs of a fleet comprised solely of combustion trucks and the hybrid fleet proposed here. The results showed that using a hybrid fleet significantly reduced waste collection costs and environmental impacts.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Aria, M., Cuccurullo, C.: bibliometrix: an R-tool for comprehensive science mapping analysis. J. Informet. 11(4), 959–975 (2017). https://doi.org/10.1016/j.joi.2017.08.007

    Article  Google Scholar 

  2. Chen, Z., et al.: Scheduling optimization of electric ready mixed concrete vehicles using an improved model-based reinforcement learning. Autom. Constr. 160, 105308 (2024). https://doi.org/10.1016/j.autcon.2024.105308

    Article  Google Scholar 

  3. Del Carmen-Niño, V., Herrera-Navarrete, R., Juárez-López, A.L., Sampedro-Rosas, M.L., Reyes-Umaña, M.: Municipal solid waste collection: challenges, strategies and perspectives in the optimization of a municipal route in a southern Mexican town. Sustainability 15(2) (2023). https://doi.org/10.3390/su15021083

  4. Doan, T.T., Bostel, N., Hà, M.H.: The vehicle routing problem with relaxed priority rules. EURO J. Transp. Logist. 10, 100039 (2021). https://doi.org/10.1016/j.ejtl.2021.100039

    Article  Google Scholar 

  5. Erdem, M.: Optimisation of sustainable urban recycling waste collection and routing with heterogeneous electric vehicles. Sustain. Urban Areas 80, 103785 (2022). https://doi.org/10.1016/j.scs.2022.103785

    Article  Google Scholar 

  6. Golden, B., Assad, A., Levy, L., Gheysens, F.: The fleet size and mix vehicle routing problem. Comput. Oper. Res. 11(1), 49–66 (1984). https://doi.org/10.1016/0305-0548(84)90007-8

    Article  Google Scholar 

  7. Guo, Y., Kelly, J.A., Clinch, J.P.: Road transport electrification - is timing everything? Implications of emissions analysis’ outcomes for climate and air policy. Transp. Res. Interdisc. Perspect. 12, 100478 (2021). https://doi.org/10.1016/j.trip.2021.100478

    Article  Google Scholar 

  8. Hatami, S., Eskandarpour, M., Chica Serrano, M., Juan Pérez, Á.A., Ouelhadj, D.: Green hybrid fleets using electric vehicles: solving the heterogeneous vehicle routing problem with multiple driving ranges and loading capacities. SORT: Stat. Oper. Res. Trans. 44(1) (2020). https://doi.org/10.2436/20.8080.02.98

  9. Liimatainen, H., van Vliet, O., Aplyn, D.: The potential of electric trucks - an international commodity-level analysis. Appl. Energy 236, 804–814 (2019). https://doi.org/10.1016/j.apenergy.2018.12.017

    Article  Google Scholar 

  10. Moazzeni, S., Tavana, M., Mostafayi Darmian, S.: A dynamic location-arc routing optimization model for electric waste collection vehicles. J. Clean. Prod. 364, 132571 (2022). https://doi.org/10.1016/j.jclepro.2022.132571

    Article  Google Scholar 

  11. Moreno-Solaz, H., Ángel Artacho-Ramírez, M., Aragonés-Beltrán, P., Cloquell-Ballester, V.A.: Sustainable selection of waste collection trucks considering feasible future scenarios by applying the stratified best and worst method. Heliyon 9(4), e15481 (2023). https://doi.org/10.1016/j.heliyon.2023.e15481

    Article  Google Scholar 

  12. Nowakowski, P., Wala, M.: Electric waste collection vehicles in Poland: a challenge or burden for local communities? Sustain. Cities Soc. 38, 101452 (2024). https://doi.org/10.1016/j.scp.2024.101452

    Article  Google Scholar 

  13. Osieczko, K., Zimon, D., Płaczek, E., Prokopiuk, I.: Factors that influence the expansion of electric delivery vehicles and trucks in EU countries. J. Environ. Manage. 296, 113177 (2021). https://doi.org/10.1016/j.jenvman.2021.113177

    Article  Google Scholar 

  14. Perianes-Rodriguez, A., Waltman, L., van Eck, N.J.: Constructing bibliometric networks: a comparison between full and fractional counting. J. Informet. 10(4), 1178–1195 (2016). https://doi.org/10.1016/j.joi.2016.10.006

    Article  Google Scholar 

  15. Shi, R., Niu, L.: A brief survey on learning based methods for vehicle routing problems. Procedia Comput. Sci. 221, 773–780 (2023). https://doi.org/10.1016/j.procs.2023.08.050. Tenth International Conference on Information Technology and Quantitative Management (ITQM 2023)

  16. Silva, A.S., et al.: Dynamic urban solid waste management system for smart cities. In: International Conference on Learning and Intelligent Optimization, pp. 178–190. Springer (2022). https://doi.org/10.1007/978-3-031-24866-5_14

  17. Silva, A.S., Lima, J., Pereira, A.I., Silva, A.M.T., Gomes, H.T.: Execution time experiments to solve capacitated vehicle routing problem, pp. 273–289. Springer, Cham (2023)

    Google Scholar 

  18. Silva, A.S., Lima, J., Silva, A.M., Gomes, H.T., Pereira, A.I.: Time-dependency of guided local search to solve the capacitated vehicle routing problem with time windows. In: International Conference on Optimization, Learning Algorithms and Applications, pp. 93–108. Springer (2024). https://doi.org/10.1007/978-3-031-53025-8_7

  19. Silva, A.S., Pereira, A.I., Lima, J., Silva, A.M.T., Gomes, H.T.: Execution time as a key parameter in the waste collection problem. In: 2023 18th Iberian Conference on Information Systems and Technologies (CISTI), pp. 1–6 (2023). https://doi.org/10.23919/CISTI58278.2023.10211886

  20. Silva, A.S., et al.: Capacitated waste collection problem solution using an open-source tool. Computers 12(1) (2023). https://doi.org/10.3390/computers12010015

  21. Silva, A., Lima, J., Pereira, A., Silva, A., Gomes, H.: System size influence on optimization of municipal solid waste collection. In: WASTES: Solutions, Treatments and Opportunities IV, pp. 252–257. CRC Press (2023). https://doi.org/10.1201/9781003345084-41

  22. Stavropoulou, F.: The consistent vehicle routing problem with heterogeneous fleet. Comput. Oper. Res. 140, 105644 (2022). https://doi.org/10.1016/j.cor.2021.105644

    Article  MathSciNet  Google Scholar 

  23. Taillard, É.D.: A heuristic column generation method for the heterogeneous fleet VRP. RAIRO-Oper. Res. 33(1), 1–14 (1999). https://doi.org/10.1051/ro:1999101

    Article  MathSciNet  Google Scholar 

  24. Yang, J., Tao, F., Zhong, Y.: Dynamic routing for waste collection and transportation with multi-compartment electric vehicle using smart waste bins. Waste Manag. Res. 40(8), 1199–1211 (2022). https://doi.org/10.1177/0734242X211069738

    Article  Google Scholar 

  25. Yu, V.F., Jewpanya, P., Redi, A.P., Tsao, Y.C.: Adaptive neighborhood simulated annealing for the heterogeneous fleet vehicle routing problem with multiple cross-docks. Comput. Oper. Res. 129, 105205 (2021). https://doi.org/10.1016/j.cor.2020.105205

    Article  MathSciNet  Google Scholar 

  26. Zhao, Y., Tatari, O.: Carbon and energy footprints of refuse collection trucks: a hybrid life cycle evaluation. Sustain. Prod. Consum. 12, 180–192 (2017). https://doi.org/10.1016/j.spc.2017.07.005

    Article  Google Scholar 

Download references

Acknowledgments

This work was supported by national funds through FCT/MCTES (PIDDAC): CeDRI, UIDB/05757/2020 (DOI: 10.54499/UIDB/05757/2020) and UIDP/05757/2020 (DOI: 10.54499/UIDB/05757/2020); CIMO, UIDB/00690/2020 (DOI: 10.54499/UIDB/00690/2020) and UIDP/00690/2020 (DOI: 10.54499/UIDP/00690/2020); SusTEC, LA/P/0007/2020 (DOI: 10.54499/LA/P/0007/2020), LSRE-LCM, UIDB/50020/2020 (DOI: 10.54499/UIDB/50020/2020) and UIDP/50020/2020 (DOI: 10.54499/UIDP/50020/2020); and ALiCE, LA/P/0045/2020 (DOI: 10.54499/LA/P/0045/2020). Adriano Silva was supported by Doctoral Grant SFRH/BD/151346/2021 financed by the Portuguese Foundation for Science and Technology (FCT), and with funds from NORTE 2020, under MIT Portugal Program. The authors are grateful to Sociedade Ponto Verde for the financial support through the project “A digitalização como ferramenta para melhorar a sustentabilidade do processo de recolha seletiva”.

Author information

Authors and Affiliations

  1. Research Centre in Digitalization and Intelligent Robotics (CeDRI), Instituto Politécnico de Bragança, Campus Santa Apolónia, 5300-253, Bragança, Portugal

    A. S. Silva, José Lima & Ana I. Pereira

  2. Centro de Investigação de Montanha (CIMO), Instituto Politécnico de Bragança, Campus Santa Apolónia, 5300-253, Bragança, Portugal

    A. S. Silva & H. T. Gomes

  3. Laboratório Associado para a Sustentabilidade e Tecnologia em Regiões de Montanha (SusTEC), Instituto Politécnico de Bragança, Campus Santa Apolónia, 5300-253, Bragança, Portugal

    A. S. Silva, José Lima, H. T. Gomes & Ana I. Pereira

  4. LSRE-LCM – Laboratory of Separation and Reaction Engineering – Laboratory of Catalysis and Materials, Faculty of Engineering, University of Porto, Rua Dr. Roberto Frias, 4200-465, Porto, Portugal

    A. S. Silva & A. M. T. Silva

  5. ALiCE – Associate Laboratory in Chemical Engineering, Faculty of Engineering, University of Porto, Rua Dr. Roberto Frias, 4200-465, Porto, Portugal

    A. S. Silva & A. M. T. Silva

Authors
  1. A. S. Silva
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. José Lima
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. A. M. T. Silva
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. H. T. Gomes
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Ana I. Pereira
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to A. S. Silva .

Editor information

Editors and Affiliations

  1. Instituto Politécnico de Bragança, Bragança, Portugal

    Ana I. Pereira

  2. Instituto Politécnico de Bragança, Bragança, Portugal

    Florbela P. Fernandes

  3. Instituto Politécnico de Bragança, Bragança, Portugal

    João P. Coelho

  4. Instituto Politécnico de Bragança, Bragança, Portugal

    João P. Teixeira

  5. Department of Electrical Engineering, Instituto Politécnico de Bragança, Bragança, Portugal

    José Lima

  6. Instituto Politécnico de Bragança, Bragança, Portugal

    Maria F. Pacheco

  7. Instituto Politécnico de Bragança, Bragança, Portugal

    Rui P. Lopes

  8. Universidad de La Laguna, San Cristóbal de La Laguna, Spain

    Santiago T. Álvarez

Rights and permissions

Reprints and permissions

Copyright information

© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Silva, A.S., Lima, J., Silva, A.M.T., Gomes, H.T., Pereira, A.I. (2024). Optimizing Waste Collection in Constrained Urban Spaces: A Hybrid Fleet Approach. In: Pereira, A.I., et al. Optimization, Learning Algorithms and Applications. OL2A 2024. Communications in Computer and Information Science, vol 2281. Springer, Cham. https://doi.org/10.1007/978-3-031-77432-4_10

Download citation

Publish with us

Policies and ethics