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dc.contributor.authorToutouh, Jamal
dc.contributor.authorRossit, Diego
dc.contributor.authorNesmachnow, Sergio
dc.date.accessioned2021-09-20T17:17:09Z
dc.date.available2021-09-20T17:17:09Z
dc.date.issued2019-06-20
dc.identifier.urihttps://hdl.handle.net/1721.1/131458
dc.description.abstractAbstract 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.en_US
dc.publisherSpringer International Publishingen_US
dc.relation.isversionofhttps://doi.org/10.1007/s10472-019-09647-5en_US
dc.rightsArticle is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.en_US
dc.sourceSpringer International Publishingen_US
dc.titleSoft computing methods for multiobjective location of garbage accumulation points in smart citiesen_US
dc.typeArticleen_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2020-09-24T21:13:53Z
dc.language.rfc3066en
dc.rights.holderSpringer Nature Switzerland AG
dspace.embargo.termsY
dspace.date.submission2020-09-24T21:13:53Z
mit.licensePUBLISHER_POLICY
mit.metadata.statusAuthority Work and Publication Information Needed


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