Soft computing methods for multiobjective location of garbage accumulation points in smart cities


This article describes the application of soft computing methods for solving the problem of locating garbage accumulation points in urban scenarios. This is a relevant problem in modern smart cities, in order to reduce negative environmental and social impacts in the waste management process, and also to optimize the available budget from the city administration to install waste bins. A specific problem model is presented, which accounts for reducing the investment costs, enhance the number of citizens served by the installed bins, and the accessibility to the system. A family of single- and multi-objective heuristics based on the PageRank method and two mutiobjective evolutionary algorithms are proposed. Experimental evaluation performed on real scenarios on the cities of Montevideo (Uruguay) and Bahía Blanca (Argentina) demonstrates the effectiveness of the proposed approaches. The methods allow computing plannings with different trade-off between the problem objectives. The computed results improve over the current planning in Montevideo and provide a reasonable budget cost and quality of service for Bahía Blanca.

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  1. 1.

    Bäck, T., Fogel, D., Michalewicz, Z. (eds.): Handbook of Evolutionary Computation. Oxford University Press (1997)

  2. 2.

    Bautista, J., Pereira, J.: Modeling the problem of locating collection areas for urban waste management. An application to the metropolitan area of Barcelona. Omega 34(6), 617–629 (2006)

    Article  Google Scholar 

  3. 3.

    Ben Brahim, M., Drira, W., Filali, F.: Roadside units placement within city-scaled area in vehicular ad-hoc networks. In: 3rd International Conference on Connected Vehicles and Expo, pp 1010–1016. IEEE, Vienna (2014)

  4. 4.

    Boskovic, G., Jovicic, N.: Fast methodology to design the optimal collection point locations and number of waste bins: A case study. Waste Manag. Res. 33(12), 1094–1102 (2015)

    Article  Google Scholar 

  5. 5.

    Broz, D., Rossit, D.A., Rossit, D.G., Cavallin, A.: The Argentinian forest sector: Opportunities and challenges in supply chain management. Uncertain Supply Chain Manag. 6(4), 375–392 (2018)

    Google Scholar 

  6. 6.

    CEMPRE: Compromiso Empresarial Para el Reciclaje. (2018) Retrieved from

  7. 7.

    Chang, N.B., Wei, Y.: Siting recycling drop-off stations in urban area by genetic algorithm-based fuzzy multiobjective nonlinear integer programming modeling. Fuzzy Set. Syst. 114(1), 133–149 (2000)

    Article  Google Scholar 

  8. 8.

    City Hall of Montevideo: Gestión de residuos. (2018) Retrieved from

  9. 9.

    Coello, C., Van Veldhuizen, D., Lamont, G.: Evolutionary Algorithms for Solving Multi-Objective Problems. Kluwer (2002)

  10. 10.

    Deakin, M., Waer, H.: From Intelligent to Smart Cities. Taylor & Francis (2012)

  11. 11.

    Deb, K.: Multi-Objective Optimization using Evolutionary Algorithms. Wiley (2001)

  12. 12.

    Di Felice, P.: Integration of spatial and descriptive information to solve the urban waste accumulation problem: A pilot study. Procedia-Social Behav. Sci. 147, 592–597 (2014)

    Article  Google Scholar 

  13. 13.

    Fortin, F., De Rainville, F., Gardner, M., Parizeau, M., Gagné, C.: DEAP: Evolutionary algorithms made easy. J. Mach. Learn. Res. 13, 2171–2175 (2012)

    MathSciNet  MATH  Google Scholar 

  14. 14.

    Ghiani, G., Laganà, D., Manni, E., Triki, C.: Capacitated location of collection sites in an urban waste management system. Waste Manag. 32(7), 1291–1296 (2012)

    Article  Google Scholar 

  15. 15.

    Ghiani, G., Manni, A., Manni, E., Toraldo, M.: The impact of an efficient collection sites location on the zoning phase in municipal solid waste management. Waste Manag. 34(11), 1949–1956 (2014)

    Article  Google Scholar 

  16. 16.

    Goulart Coelho, L., Lange, L., Coelho, H.: Multi-criteria decision making to support waste management: A critical review of current practices and methods. Waste Manag. Res. 35(1), 3–28 (2017)

    Article  Google Scholar 

  17. 17.

    Hemmelmayr, V.C., Doerner, K.F., Hartl, R.F., Vigo, D.: Models and algorithms for the integrated planning of bin allocation and vehicle routing in solid waste management. Transp. Sci. 48(1), 103–120 (2013)

    Article  Google Scholar 

  18. 18.

    Hoornweg, D., Bhada-Tata, P., Kennedy, C.: Peak waste: When is it likely to occur? J. Ind. Ecol. 19(1), 117–128 (2015)

    Article  Google Scholar 

  19. 19.

    Hutter, F., Hoos, H., Leyton-Brown, K.: Sequential model-based optimization for general algorithm configuration. In: Proceedings of the 5th International Conference on Learning and Intelligent Optimization, pp. 507–523 (2011)

    Google Scholar 

  20. 20.

    Khatoun, R., Zeadally, S.: Smart cities: Concepts, architectures, research opportunities. Commun. ACM 59(8), 46–57 (2016)

    Article  Google Scholar 

  21. 21.

    Langville, A., Meyer, C.: Google’s PageRank and Beyond: The Science of Search Engine Rankings. Princeton University Press (2011)

  22. 22.

    Lindell, M., Earle, T.: How close is close enough: Public perceptions of the risks of industrial facilities. Risk Anal. 3(4), 245–253 (1983)

    Article  Google Scholar 

  23. 23.

    Massobrio, R., Toutouh, J., Nesmachnow, S., Alba, E.: Infrastructure deployment in vehicular communication networks using a parallel multiobjective evolutionary algorithm. Int. J. Intell. Syst. 32(8), 801–829 (2017)

    Article  Google Scholar 

  24. 24.

    Megiddo, N., Tamir, A.: On the complexity of locating linear facilities in the plane. Oper. Res. Lett. 1(5), 194–197 (1982)

    MathSciNet  Article  Google Scholar 

  25. 25.

    Ministerio de Vivienda, Ordenamiento Territorial y Medio Ambiente, Uruguay: Plan de gestion de Montevideo para la recuperación de residuos de envases no retornableś (2012). Retrived from

  26. 26.

    Nesmachnow, S.: Computacion científica de alto desempeño en la Facultad de Ingeniería. Universidad de la Repúblicá. Revista de la Asociación de Ingenieros del Uruguay 61(1), 12–15 (2010)

    Google Scholar 

  27. 27.

    Nesmachnow, S.: An overview of metaheuristics: Accurate and efficient methods for optimisation. Int. J. Metaheuristics 3(4), 320–347 (2014)

    Article  Google Scholar 

  28. 28.

    Nesmachnow, S., Rossit, D.G., Toutouh, J.: Comparison of multiobjective evolutionary algorithms for prioritized urban waste collection in Montevideo, Uruguay. Electron Notes Discrete Math. 69, 93–100 (2018)

    Article  Google Scholar 

  29. 29.

    nez, M.L.I., Dubois-Lacoste, J., Pérez Cáceres, L., Stützle, T., Birattari, M.: The irace package: Iterated racing for automatic algorithm configuration. Oper. Res. Perspect. 3, 43–58 (2016)

    MathSciNet  Article  Google Scholar 

  30. 30.

    Pėres, M., Ruiz, G., Nesmachnow, S., Olivera, A.C.: Multiobjective evolutionary optimization of traffic flow and pollution in Montevideo, Uruguay. Appl. Soft Comput. 70, 472–485 (2018)

    Article  Google Scholar 

  31. 31.

    Planta Piloto de Ingeniería Química UNS-CONICET: Análisis estadístico de los residuos sólidos domiciliarios de Bahía Blanca (2013). Internal document

  32. 32.

    Purkayastha, D., Majumder, M., Chakrabarti, S.: Collection and recycle bin location-allocation problem in solid waste management: A review. Pollution 1(2), 175–191 (2015)

    Google Scholar 

  33. 33.

    Rossit, D., Nesmachnow, S., Toutouh, J.: Municipal solid waste management in smart cities: Facility location of community bins. In: I Ibero-American Congress of Smart Cities ICSC-CITIES, pp. 102–115 (2018)

    Google Scholar 

  34. 34.

    Toutouh, J., Rossit, D.G., Nesmachnow, S.: Computational intelligence for locating garbage accumulation points in urban scenarios. In: Learning and Intelligent Optimization Conference LION. Kalamata (2018)

  35. 35.

    Valeo, C., Baetz, B., Tsanis, I.: Location of recycling depots with GIS. J. Urban Plan. Develop. 124(2), 93–99 (1998)

    Article  Google Scholar 

  36. 36.

    Wilson, D.C., Velis, C., Cheeseman, C.: Role of informal sector recycling in waste management in developing countries. Habitat Int. 30(4), 797–808 (2006)

    Article  Google Scholar 

  37. 37.

    Zitzler, E., Laumanns, M., Thiele, L. In: Giannakoglou, K., Tsahalis, D., Périaux, J., Papailiou, K., Fogarty, T. (eds.) Evolutionary Methods for Design Optimization and Control with Applications to Industrial Problems, pp 95–100 (2001)

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We would like to thank the anonymous reviewers for their insightful comments on the paper that led us to an improvement of this work.

The work of J. Toutouh has been partially funded by Ministerio de Economía, Industria y Competitividad, Gobierno de España, and European Regional Development Fund grant numbers TIN2016-81766-REDT (, and TIN2017-88213-R ( European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 799078. Universidad de Málaga, Campus Internacional de Excelencia Andalucía TECH.

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Correspondence to Jamal Toutouh.

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Toutouh, J., Rossit, D. & Nesmachnow, S. Soft computing methods for multiobjective location of garbage accumulation points in smart cities. Ann Math Artif Intell 88, 105–131 (2020).

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  • Computational intelligence
  • Waste management
  • Smart cities

Mathematics Subject Classification (2010)

  • 90C59