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

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Abstract

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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Acknowledgements

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 (http://cirti.es), and TIN2017-88213-R (http://6city.lcc.uma.es). 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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Authors and Affiliations

  1. Massachusetts Institute of Technology, Cambridge, MA, USA

    Jamal Toutouh

  2. DI, Universidad Nacional del Sur, Buenos Aires, Argentina

    Diego Rossit

  3. CONICET, Buenos Aires, Argentina

    Diego Rossit

  4. Universidad de la República, Montevideo, Uruguay

    Sergio Nesmachnow

Authors
  1. Jamal Toutouh
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  2. Diego Rossit
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  3. Sergio Nesmachnow
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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). https://doi.org/10.1007/s10472-019-09647-5

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  • DOI: https://doi.org/10.1007/s10472-019-09647-5

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