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dc.contributor.author
Cavallin, Antonella
dc.contributor.author
Frutos, Mariano
dc.contributor.author
Vigier, Hernan Pedro
dc.contributor.author
Rossit, Diego Gabriel
dc.date.available
2023-01-23T14:13:37Z
dc.date.issued
2017
dc.identifier.citation
Cavallin, Antonella; Frutos, Mariano; Vigier, Hernan Pedro; Rossit, Diego Gabriel; An integrated model of Data Envelopment Analysis and Artificial Neural Networks for improving efficiency in the municipal solid waste management; IGI Global; 1; 1; 2017; 206-231
dc.identifier.isbn
9781522529903
dc.identifier.issn
2327-3275
dc.identifier.uri
http://hdl.handle.net/11336/185267
dc.description.abstract
In the last decades, integral municipal solid waste management (IMSWM) has become one of the most challenging areas for local governmental authorities, which have struggled to lay down sustainable and financially stable policies for the sector. In this paper a model that evaluates the efficiency of IMSWMs through a combination of Data Envelopment Analysis (DEA) and an Artificial Neural Network (ANN) is presented. In a first stage, applying DEA, municipal administrations are classified according to the efficiency of their garbage processing systems. This is done in order to infer what modifications are necessary to make garbage handling more efficient. In a second stage, an ANN is used for predicting the necessary resources needed to make the waste processing system efficient. This methodology is applied on a toy model with 50 towns as well as on a real-world case of 21 cities. The results show the usefulness of the model for the evaluation of relative efficiency and for guiding the improvement of the system.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
IGI Global
dc.rights
info:eu-repo/semantics/restrictedAccess
dc.rights
Atribución-NoComercial-CompartirIgual 2.5 Argentina (CC BY-NC-SA 2.5 AR)
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.subject
ARTIFICIAL NEURAL NETWORK
dc.subject
DATA ENVELOPMENT ANALYSIS
dc.subject
SOLID WASTE
dc.subject
EFFICIENCY
dc.subject
HYBRID MODEL
dc.subject.classification
Otras Ingenierías y Tecnologías
dc.subject.classification
Otras Ingenierías y Tecnologías
dc.subject.classification
INGENIERÍAS Y TECNOLOGÍAS
dc.title
An integrated model of Data Envelopment Analysis and Artificial Neural Networks for improving efficiency in the municipal solid waste management
dc.type
info:eu-repo/semantics/publishedVersion
dc.type
info:eu-repo/semantics/bookPart
dc.type
info:ar-repo/semantics/parte de libro
dc.date.updated
2021-09-09T16:45:16Z
dc.identifier.eissn
2327-3283
dc.journal.volume
1
dc.journal.number
1
dc.journal.pagination
206-231
dc.journal.pais
Estados Unidos
dc.journal.ciudad
Hershey
dc.description.fil
Fil: Cavallin, Antonella. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones Económicas y Sociales del Sur. Universidad Nacional del Sur. Departamento de Economía. Instituto de Investigaciones Económicas y Sociales del Sur; Argentina
dc.description.fil
Fil: Frutos, Mariano. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones Económicas y Sociales del Sur. Universidad Nacional del Sur. Departamento de Economía. Instituto de Investigaciones Económicas y Sociales del Sur; Argentina
dc.description.fil
Fil: Vigier, Hernan Pedro. Provincia de Buenos Aires. Dirección General de Cultura y Educación. Universidad Provincial del Sudoeste. Centro de Emprendedorismo y Desarrollo Territorial Sustentable; Argentina
dc.description.fil
Fil: Rossit, Diego Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones Económicas y Sociales del Sur. Universidad Nacional del Sur. Departamento de Economía. Instituto de Investigaciones Económicas y Sociales del Sur; Argentina
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://www.igi-global.com/chapter/an-integrated-model-of-data-envelopment-analysis-and-artificial-neural-networks-for-improving-efficiency-in-the-municipal-solid-waste-management/190161
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.4018/978-1-5225-2990-3.ch009
dc.conicet.paginas
812
dc.source.titulo
Emergent Research on the Application of Optimization Algorithms
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