Fluvial restoration by applying multi-target genetic algorithms
Analyzing the processes of environmental resource management, it is clear the increased concern of the environment, configured as a factor (in conjunction with economic and technological criteria, etc.) to take into account in decision-making processes. This combination of factors of different natur...
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| Lenguaje: | Español |
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Escuela de Perfeccionamiento en Investigación Operativa
2018
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| Acceso en línea: | https://revistas.unc.edu.ar/index.php/epio/article/view/20306 |
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I10-R359-article-203062018-06-14T15:43:22Z Fluvial restoration by applying multi-target genetic algorithms Restauración fluvial aplicando algoritmos genéticos multiobjetivo Údias, Ángel Redchuk, Andrés Cano, Javier Galbiati, Lorenzo algoritmo genético multicriterio coste-eficacia directiva marco del agua métricas genetic algorithm multicriteria cost-efficacy water framework directive metrics Analyzing the processes of environmental resource management, it is clear the increased concern of the environment, configured as a factor (in conjunction with economic and technological criteria, etc.) to take into account in decision-making processes. This combination of factors of different nature complicates the quantitative analysis of the alternatives to which the decision maker has to face, especially if one takes into account environmental factors that typically, by their very nature, are often difficult to compare and quantify.The use of a system of multicriteria decision support that integrate engine optimization as a multiobjective genetic algorithm is suitable to apply to the environmental issues presented in this article. Analizando los procesos de gestión de los recursos ambientales, es evidente el aumento de la preocupación por el medio ambiente, configurándolo como un factor más (conjuntamente con criterios económicos, tecnológicos, etc.) a tener en cuenta en los procesos de toma de decisiones. Esta combinación de factores de diversa naturaleza complica el análisis cuantitativo de las alternativas a las que se ha de enfrentar el decisor, más aún si se tiene en cuenta que típicamente los factores ambientales, por su propia naturaleza, suelen ser de difícil comparación y cuantificación.La utilización de un sistema de ayuda a la decisión multicriterio que integran como motor de optimización un algoritmo genético multiobjetivo resulta idónea para la aplicación a la problemática medio ambiental que se presenta en este artículo. Escuela de Perfeccionamiento en Investigación Operativa 2018-06-14 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://revistas.unc.edu.ar/index.php/epio/article/view/20306 Revista de la Escuela de Perfeccionamiento en Investigación Operativa; Vol. 21 Núm. 34 (2013): Noviembre; 62-80 1853-9777 0329-7322 spa https://revistas.unc.edu.ar/index.php/epio/article/view/20306/19950 |
| institution |
Universidad Nacional de Córdoba |
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I-10 |
| repository_str |
R-359 |
| container_title_str |
Revista de la Escuela de Perfeccionamiento en Investigación Operativa |
| language |
Español |
| format |
Artículo revista |
| topic |
algoritmo genético multicriterio coste-eficacia directiva marco del agua métricas genetic algorithm multicriteria cost-efficacy water framework directive metrics |
| spellingShingle |
algoritmo genético multicriterio coste-eficacia directiva marco del agua métricas genetic algorithm multicriteria cost-efficacy water framework directive metrics Údias, Ángel Redchuk, Andrés Cano, Javier Galbiati, Lorenzo Fluvial restoration by applying multi-target genetic algorithms |
| topic_facet |
algoritmo genético multicriterio coste-eficacia directiva marco del agua métricas genetic algorithm multicriteria cost-efficacy water framework directive metrics |
| author |
Údias, Ángel Redchuk, Andrés Cano, Javier Galbiati, Lorenzo |
| author_facet |
Údias, Ángel Redchuk, Andrés Cano, Javier Galbiati, Lorenzo |
| author_sort |
Údias, Ángel |
| title |
Fluvial restoration by applying multi-target genetic algorithms |
| title_short |
Fluvial restoration by applying multi-target genetic algorithms |
| title_full |
Fluvial restoration by applying multi-target genetic algorithms |
| title_fullStr |
Fluvial restoration by applying multi-target genetic algorithms |
| title_full_unstemmed |
Fluvial restoration by applying multi-target genetic algorithms |
| title_sort |
fluvial restoration by applying multi-target genetic algorithms |
| description |
Analyzing the processes of environmental resource management, it is clear the increased concern of the environment, configured as a factor (in conjunction with economic and technological criteria, etc.) to take into account in decision-making processes. This combination of factors of different nature complicates the quantitative analysis of the alternatives to which the decision maker has to face, especially if one takes into account environmental factors that typically, by their very nature, are often difficult to compare and quantify.The use of a system of multicriteria decision support that integrate engine optimization as a multiobjective genetic algorithm is suitable to apply to the environmental issues presented in this article. |
| publisher |
Escuela de Perfeccionamiento en Investigación Operativa |
| publishDate |
2018 |
| url |
https://revistas.unc.edu.ar/index.php/epio/article/view/20306 |
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2024-09-03T22:23:14Z |
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2024-09-03T22:23:14Z |
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