Por favor, use este identificador para citar o enlazar este ítem:
https://hdl.handle.net/11000/6259
Registro completo de metadatos
Campo DC | Valor | Lengua/Idioma |
---|---|---|
dc.contributor.author | González, Martín | - |
dc.contributor.author | López Espín, José Juan | - |
dc.contributor.author | Aparicio, Juan | - |
dc.contributor.author | Giménez, Domingo | - |
dc.contributor.author | Talbi, El-Ghazali | - |
dc.contributor.other | Departamentos de la UMH::Estadística, Matemáticas e Informática | es |
dc.date.accessioned | 2020-09-01T10:29:29Z | - |
dc.date.available | 2020-09-01T10:29:29Z | - |
dc.date.created | 2017-06-08 | - |
dc.date.issued | 2020-09-01 | - |
dc.identifier.uri | http://hdl.handle.net/11000/6259 | - |
dc.description.abstract | Data Envelopment Analysis (DEA) is a nonparametric methodology for estimating technical efficiency of a set of Decision Making Units (DMUs) from a dataset of inputs and outputs. This paper is devoted to computational aspects of DEA models under the application of the Principle of Least Action. This principle guarantees that the efficient closest targets are determined as benchmarks for each assessed unit. Usually, these models have been addressed in the literature by applying unsatisfactory techniques, based fundamentally on combinatorial NPhard problems. Recently, some heuristics have been developed to partially solve these DEA models. This paper improves the heuristic methods used in previous works by applying a combination of metaheuristics and an exact method. Also, a parameterized scheme of metaheuristics is developed in order to implement metaheuristics and hybridations/combinations, adapting them to the particular problem proposed here. In this scheme, some parameters are used to study several types of metaheuristics, like Greedy Random Adaptative Search Procedure, Genetic Algorithms or Scatter Search. The exact method is included inside the metaheuristic to solve the particular model presented in this paper. A hyperheuristic is used on top of the parameterized scheme in order to search, in the space of metaheuristics, for metaheuristics that provide solutions close to the optimum. The method is competitive with exact methods, obtaining fitness close to the optimum with low computational time | es |
dc.description.sponsorship | J. Aparicio and M. González thank the financial support from the Spanish ‘Ministerio de Economa, Industria y Competitividad’ (MINECO), the ‘Agencia Estatal de Investigacion’ and the ‘Fondo Europeo de Desarrollo Regional’ under grant MTM2016-79765-P (AEI/FEDER, UE). | - |
dc.description.sponsorship | Additionally, D. Giméenez thanks the financial support from the Spanish MINECO, as well as by European Commission FEDER funds, under grant TIN2015-66972-C5-3-R. | - |
dc.format | application/pdf | es |
dc.format.extent | 8 | es |
dc.language.iso | eng | es |
dc.rights | info:eu-repo/semantics/openAccess | es |
dc.subject | Mathematical model | es |
dc.subject | Computational modeling | es |
dc.subject | Data envelopment analysis | es |
dc.subject | Mathematical programming | es |
dc.subject | Operations research | es |
dc.subject | Genetic algorithms | es |
dc.subject | Production | es |
dc.subject.other | 517 - Análisis matemático | es |
dc.title | A parameterized scheme of metaheuristics with exact methods for determining the Principle of Least Action in Data Envelopment Analysis | es |
dc.type | info:eu-repo/semantics/article | es |
dc.identifier.doi | 10.1109/CEC.2017.7969364 | - |
dc.relation.publisherversion | https://doi.org/10.1109/CEC.2017.7969364 | - |
![Vista previa](/retrieve/33d6e36c-23f4-4f31-b2e9-19accb78593e/11-Gonzalez_etal2017_IEEE.pdf.jpg)
Ver/Abrir:
11-Gonzalez_etal2017_IEEE.pdf
856,86 kB
Adobe PDF
Compartir:
La licencia se describe como: Atribución-NonComercial-NoDerivada 4.0 Internacional.