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Computational Intelligence for Locating Garbage Accumulation Points in Urban Scenarios

  • Jamal Toutouh
  • Diego Rossit
  • Sergio Nesmachnow
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11353)

Abstract

This article presents computational intelligence methods for solving the problem of locating garbage accumulation points in urban scenarios, which is a relevant problem in nowadays smart cities to optimize budget and reduce negative environmental and social impacts. The problem model considers reducing the investment costs, enhance the proportion of citizens served by bins, and the accessibility to the system. A family of heuristics based on the generic PageRank schema and a mutiobjective evolutionary algorithm are proposed. Experimental evaluation performed on real scenarios on the city of Montevideo, Uruguay, demonstrates the effectiveness of the proposed approaches. The methods allow computing plannings with different trade-off between the problem objectives and improving over the current planning.

Keywords

Computational intelligence Waste management Smart cities 

Notes

Acknowledgments

The work of J. Toutouh has been partially funded by MINECO and FEDER projects TIN2014-57341-R, TIN2016-81766-REDT, and TIN2017-88213-R, Spain. University of Malaga. International Campus of Excellence Andalucia TECH. The work of S. Nesmachnow is partly supported by ANII and PEDECIBA, Uruguay. The work of D. Rossit is partly funded by the Department of Engineering of Universidad Nacional del Sur, Argentina.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Jamal Toutouh
    • 1
  • Diego Rossit
    • 2
  • Sergio Nesmachnow
    • 3
  1. 1.Universidad de MálagaMálagaSpain
  2. 2.Universidad Nacional del Sur-CONICETBahía BlancaArgentina
  3. 3.Universidad de la RepúblicaMontevideoUruguay

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