Skip to main content
Springer Nature Link
Log in

Dynamic Urban Solid Waste Management System for Smart Cities

  • Conference paper
  • First Online:
Learning and Intelligent Optimization (LION 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13621))

Included in the following conference series:

Abstract

Increasing population in cities combined with efforts to obtain more sustainable living spaces will require a smarter Solid Waste Management System (SWMS). A critical step in SWMS is the collection of wastes, generally associated with expensive costs faced by companies or municipalities in this sector. Some studies are being developed for the optimization of waste collection routes, but few consider inland cities as model regions. Here, the model region considered for the route optimization using Guided Local Search (GLS) algorithm was Bragança, a city in the northeast region of Portugal. The algorithm used in this work is available in open-source Google OR-tools. Results show that waste collection efficiency is affected by the upper limit of waste in dumpsters. Additionally, it is demonstrated the importance of dynamic selection of dumpsters. For instance, efficiency decreased 10.67% for the best upper limit compared to the traditional collection in the regular selection of dumpsters (levels only). However, an improvement of 50.45% compared to traditional collection was observed using dynamic selection of dumpsters to be collected. In other words, collection cannot be improved only by letting dumpsters reach 90% of waste level. In fact, strategies such as the dynamic selection here presented, can play an important role to save resources in a SWMS.

Supported by Fundação para Ciência e a Tecnologia and MIT Portugal Program.

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. Anagnostopoulos, T., et al.: Challenges and opportunities of waste management in IoT-enabled smart cities: a survey. IEEE Trans. Sustain. Comput. 2(3), 275–289 (2017). https://doi.org/10.1109/TSUSC.2017.2691049

    Article  Google Scholar 

  2. Tirkolaee, E.B., Abbasian, P., Soltani, M., Ghaffarian, S.A.: Developing an applied algorithm for multi-trip vehicle routing problem with time windows in urban waste collection: a case study. Waste Manage. Res. 37(1), 4–13 (2019). https://doi.org/10.1177/0734242X18807001

  3. Barbucha, D.: An agent-based guided local search for the capacited vehicle routing problem. In: O’Shea, J., Nguyen, N.T., Crockett, K., Howlett, R.J., Jain, L.C. (eds.) KES-AMSTA 2011. LNCS (LNAI), vol. 6682, pp. 476–485. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-22000-5_49

    Chapter  Google Scholar 

  4. Elshaer, R., Awad, H.: A taxonomic review of metaheuristic algorithms for solving the vehicle routing problem and its variants. Comput. Indus. Eng. 140, 106242 (2020). https://doi.org/10.1016/j.cie.2019.106242

    Article  Google Scholar 

  5. Erdinç, O., Yetilmezsoy, K., Erenoğlu, A.K., Erdinç, O.: Route optimization of an electric garbage truck fleet for sustainable environmental and energy management. J. Clean. Prod. 234, 1275–1286 (2019). https://doi.org/10.1016/j.jclepro.2019.06.295

    Article  Google Scholar 

  6. Esmaeilian, B., Wang, B., Lewis, K., Duarte, F., Ratti, C., Behdad, S.: The future of waste management in smart and sustainable cities: a review and concept paper. Waste Manage. 81, 177–195 (2018). https://doi.org/10.1016/j.wasman.2018.09.047

    Article  Google Scholar 

  7. Ferreira, J.A.O.: Optimização do Processo de Recolha de Resíduos: Desenvolvimento de Ferramentas de Investigação Operacional para o Problema de Orientação de Equipas com Multi-Restrições. Ph. D. thesis, Universidade do Minho (Portugal) (2015)

    Google Scholar 

  8. Ferrer, J., Alba, E.: BIN-CT: Urban waste collection based on predicting the container fill level. Biosystems 186, 103962 (2019). https://doi.org/10.1016/j.biosystems.2019.04.006

    Article  Google Scholar 

  9. Grakova, E., Slaninová, K., Martinovič, J., Křenek, J., Hanzelka, J., Svatoň, V.: Waste collection vehicle routing problem on HPC infrastructure. In: Saeed, K., Homenda, W. (eds.) CISIM 2018. LNCS, vol. 11127, pp. 266–278. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-99954-8_23

    Chapter  Google Scholar 

  10. Gruler, A., Quintero-Araújo, C.L., Calvet, L., Juan, A.A.: Waste collection under uncertainty: a simheuristic based on variable neighbourhood search. Europ. J. Indus. Eng. 11(2), 228–255 (2017)

    Article  Google Scholar 

  11. Hatamleh, R., Jamhawi, M., Al-Kofahi, S., Hijazi, H.: The use of a GIS system as a decision support tool for municipal solid waste management planning: the case study of al Nuzha district, Irbid, Jordan. Procedia Manufact. 44, 189–196 (2020). https://doi.org/10.1016/j.promfg.2020.02.221

    Article  Google Scholar 

  12. Karakatič, S.: Optimizing nonlinear charging times of electric vehicle routing with genetic algorithm. Expert Syst. Appl. 164, 114039 (2021). https://doi.org/10.1016/j.eswa.2020.114039

    Article  Google Scholar 

  13. Khachay, M., Ogorodnikov, Y.: PTAS For the Euclidean capacitated vehicle routing problem with time windows. In: Matsatsinis, N.F., Marinakis, Y., Pardalos, P. (eds.) LION 2019. LNCS, vol. 11968, pp. 224–230. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-38629-0_18

    Chapter  Google Scholar 

  14. Le, T.D.C., Nguyen, D.D., Oláh, J., Pakurár, M.: Optimal vehicle route schedules in picking up and delivering cargo containers considering time windows in logistics distribution networks: a case study. Prod. Eng. Archives 26(4), 174–184 (2020). https://doi.org/10.30657/pea.2020.26.31

    Article  Google Scholar 

  15. Lu, X., Pu, X., Han, X.: Sustainable smart waste classification and collection system: a bi-objective modeling and optimization approach. J. Clean. Prod. 276, 124183 (2020). https://doi.org/10.1016/j.jclepro.2020.124183

    Article  Google Scholar 

  16. Ma, Y., Zhang, W., Feng, C., Lev, B., Li, Z.: A bi-level multi-objective location-routing model for municipal waste management with obnoxious effects. Waste Manage. 135, 109–121 (2021). https://doi.org/10.1016/j.wasman.2021.08.034

    Article  Google Scholar 

  17. Mahmood, I., Idwan, S., Matar, I., Zubairi, J.A.: Experiments in routing vehicles for municipal services. In: 2018 International Conference on High Performance Computing & Simulation (HPCS), pp. 993–999. IEEE (2018). https://doi.org/10.1109/HPCS.2018.00156

  18. Mofid-Nakhaee, E., Barzinpour, F.: A multi-compartment capacitated arc routing problem with intermediate facilities for solid waste collection using hybrid adaptive large neighborhood search and whale algorithm. Waste Manage. Res. 37(1), 38–47 (2019). https://doi.org/10.1177/0734242X18801186

    Article  Google Scholar 

  19. Nirde, K., Mulay, P.S., Chaskar, U.M.: IoT based solid waste management system for smart city. In: 2017 International Conference on Intelligent Computing and Control Systems (ICICCS), pp. 666–669. IEEE (2017). https://doi.org/10.1109/ICCONS.2017.8250546

  20. do Nordeste, R.: Relatório de Sustentabilidade 2019. https://www.residuosdonordeste.pt/documentos/ (2019)

  21. O’Dwyer, E., Pan, I., Acha, S., Shah, N.: Smart energy systems for sustainable smart cities: current developments, trends and future directions. Appl. Energy 237, 581–597 (2019). https://doi.org/10.1016/j.apenergy.2019.01.024

    Article  Google Scholar 

  22. Pardalos, P.M.: Artificial intelligence, machine learning, and optimization tools for smart cities: designing for sustainability. Springer Nature (2022). https://doi.org/10.1007/978-3-030-84459-2

  23. Paul, A., Kumar, R.S., Rout, C., Goswami, A.: Designing a multi-depot multi-period vehicle routing problem with time window: hybridization of tabu search and variable neighbourhood search algorithm. Sadhana 46(3), 1–11 (2021). https://doi.org/10.1007/s12046-021-01693-2

  24. Ramalho, M.S., Rossetti, R.J., Cacho, N., Souza, A.: SmartGC: a software architecture for garbage collection in smart cities. Int. J. Bio-Inspired Comput. 16(2), 79–93 (2020)

    Article  Google Scholar 

  25. Rassia, S., Pardalos, P.: Smart city networks. Springer (2017).https://doi.org/10.1007/978-3-319-61313-0

  26. Rassia, S.T., Pardalos, P.M.: Sustainable environmental design in architecture: impacts on health, vol. 56. Springer Science & Business Media (2012). https://doi.org/10.1007/978-1-4419-0745-5

  27. Rassia, S.T., Pardalos, P.M. (eds.): Future city architecture for optimal living. SOIA, vol. 102. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-15030-7

  28. Shah, P.J., Anagnostopoulos, T., Zaslavsky, A., Behdad, S.: A stochastic optimization framework for planning of waste collection and value recovery operations in smart and sustainable cities. Waste Manage. 78, 104–114 (2018). https://doi.org/10.1016/j.wasman.2018.05.019

    Article  Google Scholar 

  29. Vu, H.L., Bolingbroke, D., Ng, K.T.W., Fallah, B.: Assessment of waste characteristics and their impact on GIS vehicle collection route optimization using ANN waste forecasts. Waste Manage. 88, 118–130 (2019). https://doi.org/10.1016/j.wasman.2019.03.037

    Article  Google Scholar 

  30. Yousefloo, A., Babazadeh, R.: Designing an integrated municipal solid waste management network: a case study. J. Clean. Prod. 244, 118824 (2020). https://doi.org/10.1016/j.jclepro.2019.118824

    Article  Google Scholar 

Download references

Acknowledgements

Adriano Silva was supported by FCT-MIT Portugal PhD grant SFRH/BD/151346/2021, and Thadeu Brito was supported by FCT PhD grant SFRH/BD/08598/2020. This work was financially supported by UIDB/057 57/2020 (CeDRI), UIDB/00690/2020 (CIMO), LA/P/0045/2020 (ALiCE), UID B/500 20/2020, UI- DP/50020/2020 (LSRE-LCM) and funded by national funds through FCT/MCTES (PIDDAC). Jose L. Diaz de Tuesta acknowledges the financial support through the program of Attraction de Talento of Atraccion al Talento of the Comunidad de Madrid (Spain) for the individual research grant 2020-T2/AMB-19836.

Author information

Authors and Affiliations

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

    Adriano S. Silva, Thadeu Brito, José Lima & Ana I. Pereira

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

    Adriano S. Silva, Jose L. Diaz de Tuesta & Helder T. Gomes

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

    Adriano S. Silva & Adrián M. T. Silva

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

    Adriano S. Silva & Adrián M. T. Silva

  5. Department of Chemical and Environmental Technology, ESCET, Rey Juan Carlos University, Madrid, Spain

    Jose L. Diaz de Tuesta

Authors
  1. Adriano S. Silva
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Thadeu Brito
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jose L. Diaz de Tuesta
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. José Lima
    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

  6. Adrián M. T. Silva
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Helder T. Gomes
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Adriano S. Silva .

Editor information

Editors and Affiliations

  1. SBA Research, Vienna, Austria

    Dimitris E. Simos

  2. Moscow Aviation Institute (National Research University), Moscow, Russia

    Varvara A. Rasskazova

  3. Università degli Studi di Milano-Bicocca, Milan, Italy

    Francesco Archetti

  4. Wilfrid Laurier University, Waterloo, ON, Canada

    Ilias S. Kotsireas

  5. University of Florida, Gainesville, FL, USA

    Panos M. Pardalos

Rights and permissions

Reprints and permissions

Copyright information

© 2022 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Silva, A.S. et al. (2022). Dynamic Urban Solid Waste Management System for Smart Cities. In: Simos, D.E., Rasskazova, V.A., Archetti, F., Kotsireas, I.S., Pardalos, P.M. (eds) Learning and Intelligent Optimization. LION 2022. Lecture Notes in Computer Science, vol 13621. Springer, Cham. https://doi.org/10.1007/978-3-031-24866-5_14

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-24866-5_14

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-24865-8

  • Online ISBN: 978-3-031-24866-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics