Complexity Indicators applied to the Job Shop Scheduling Problem to discriminate the best Algorithm
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| Formato: | Artículo científico |
| Lenguaje: | en |
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International Journal of Combinatorial Optimization Problems and Informatics
2011
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| _version_ | 1876458877866737664 |
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| author | Jorge A. Ruiz-Vanoye |
| author_facet | Jorge A. Ruiz-Vanoye |
| contents | Complexity Indicators applied to the Job Shop Scheduling Problem to discriminate the best Algorithm Jorge A. Ruiz-Vanoye Ocotlán Díaz-Parra José C. Zavala-Díaz Computación JSSP discriminant analysis complexity indicators In this paper, we propose the application of discriminant analysis to select appropriately the algorithm that better solves an instance of the Job Shop Scheduling Problem. The discriminant analysis was used as a method of machine learning to find the relation between the characteristics of the problem (complexity indicators) and the performance of algorithms. The prediction of the classification obtained of the discriminant analysis was 60%. 2011 artículo científico 2007-1558 https://www.redalyc.org/articulo.oa?id=265219635003 en http://www.redalyc.org/revista.oa?id=2652 International Journal of Combinatorial Optimization Problems and Informatics application/pdf International Journal of Combinatorial Optimization Problems and Informatics International Journal of Combinatorial Optimization Problems and Informatics (México) Num.3 Vol.2 |
| format | Artículo científico |
| id | redalyc_265219635003 |
| institution | Redalyc |
| language | en |
| publishDate | 2011 |
| publisher | International Journal of Combinatorial Optimization Problems and Informatics |
| spellingShingle | Complexity Indicators applied to the Job Shop Scheduling Problem to discriminate the best Algorithm Jorge A. Ruiz-Vanoye Computación JSSP discriminant analysis complexity indicators Complexity Indicators applied to the Job Shop Scheduling Problem to discriminate the best Algorithm Jorge A. Ruiz-Vanoye Ocotlán Díaz-Parra José C. Zavala-Díaz Computación JSSP discriminant analysis complexity indicators In this paper, we propose the application of discriminant analysis to select appropriately the algorithm that better solves an instance of the Job Shop Scheduling Problem. The discriminant analysis was used as a method of machine learning to find the relation between the characteristics of the problem (complexity indicators) and the performance of algorithms. The prediction of the classification obtained of the discriminant analysis was 60%. 2011 artículo científico 2007-1558 https://www.redalyc.org/articulo.oa?id=265219635003 en http://www.redalyc.org/revista.oa?id=2652 International Journal of Combinatorial Optimization Problems and Informatics application/pdf International Journal of Combinatorial Optimization Problems and Informatics International Journal of Combinatorial Optimization Problems and Informatics (México) Num.3 Vol.2 |
| title | Complexity Indicators applied to the Job Shop Scheduling Problem to discriminate the best Algorithm |
| topic | Computación JSSP discriminant analysis complexity indicators |
| url | https://www.redalyc.org/articulo.oa?id=265219635003 |