2010
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| 1. | Pérez-Ortega, Joaquín; R., Rodolfo A. Pazos; Ruiz-Vanoye, Jorge A.; Frausto-Solís, Juan; González-Barbosa, Juan J.; Fraire-Huacuja, Hector J.; Díaz-Parra, Ocotlán A Genetic Distance Metric to Discriminate the Selection of Algorithms for General ATSP Problem Journal Article In: Journal of Intelligent & Fuzzy Systems, vol. 21, no. 1-2, pp. 57-64, 2010, ISSN: 1064-1246. @article{JCR10,
title = {A Genetic Distance Metric to Discriminate the Selection of Algorithms for General ATSP Problem},
author = {Joaquín Pérez-Ortega and Rodolfo A. Pazos R. and Jorge A. Ruiz-Vanoye and Juan Frausto-Solís and Juan J. González-Barbosa and Hector J. Fraire-Huacuja and Ocotlán Díaz-Parra},
url = {http://content.iospress.com/articles/journal-of-intelligent-and-fuzzy-systems/ifs00435},
doi = {10.3233/IFS-2010-0435},
issn = {1064-1246},
year = {2010},
date = {2010-02-07},
journal = {Journal of Intelligent & Fuzzy Systems},
volume = {21},
number = {1-2},
pages = {57-64},
abstract = {The only metric that had existed so far to determine the best algorithm for solving an general Asymmetric Traveling Salesman Problem (ATSP) instance is based on the number of cities; nevertheless, it is not sufficiently adequate for discriminating the best algorithm for solving an ATSP instance, thus the necessity for devising a new metric through the use of data-mining techniques. In this paper we propose: (1) the use of a genetic distance metric for improving the selection of the algorithms that best solve a given instance of the ATSP and (2) the use of discriminant analysis as a means for predictive learning (data-mining techniques) aiming at selecting meta-heuristic algorithms.},
keywords = {Algorithms, Papers in the Science Citation Index Expanded},
pubstate = {published},
tppubtype = {article}
}
The only metric that had existed so far to determine the best algorithm for solving an general Asymmetric Traveling Salesman Problem (ATSP) instance is based on the number of cities; nevertheless, it is not sufficiently adequate for discriminating the best algorithm for solving an ATSP instance, thus the necessity for devising a new metric through the use of data-mining techniques. In this paper we propose: (1) the use of a genetic distance metric for improving the selection of the algorithms that best solve a given instance of the ATSP and (2) the use of discriminant analysis as a means for predictive learning (data-mining techniques) aiming at selecting meta-heuristic algorithms. |
2009
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| 2. | Cruz-Chávez, Marco A.; Díaz-Parra, Ocotlán; Zavala-Díaz, José C. . Un mecanismo de vecindad con búsqueda local y algoritmo genético para el problema de transporte con ventanas de tiempo Journal Article In: Programación Matemática y Software, vol. 1, no. 1, pp. 90-109, 2009, ISSN: 2007-3283. @article{OJ3,
title = {. Un mecanismo de vecindad con búsqueda local y algoritmo genético para el problema de transporte con ventanas de tiempo},
author = {Marco A. Cruz-Chávez and Ocotlán Díaz-Parra and José C. Zavala-Díaz},
url = {http://campusv.uaem.mx/revista_os/articulos/vol1no1articulo6.pdf},
issn = {2007-3283},
year = {2009},
date = {2009-02-07},
journal = {Programación Matemática y Software},
volume = {1},
number = {1},
pages = {90-109},
keywords = {Algorithms, other Index},
pubstate = {published},
tppubtype = {article}
}
|
2008
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| 3. | Ruiz-Vanoye, Jorge A.; Díaz-Parra, Ocotlán; N., Vanesa Landero A Metric to Discriminate the Selection of Algorithms for General Problem ATSP Book Chapter In: I., Lovrek; R.J., Howlett; L.C., Jain (Ed.): vol. 5177, pp. 106-113, Springer, Berlin, Heidelberg, 2008, ISBN: 978-3-540-85562-0. @inbook{BC1,
title = {A Metric to Discriminate the Selection of Algorithms for General Problem ATSP},
author = {Jorge A. Ruiz-Vanoye and Ocotlán Díaz-Parra and Vanesa Landero N.},
editor = {Lovrek I. and Howlett R.J. and Jain L.C.},
url = {https://link.springer.com/chapter/10.1007%2F978-3-540-85563-7_19},
doi = {10.1007/978-3-540-85563-7_19},
isbn = {978-3-540-85562-0},
year = {2008},
date = {2008-02-07},
volume = {5177},
pages = {106-113},
publisher = {Springer, Berlin, Heidelberg},
series = { Lecture Notes in Computer Science},
abstract = {In this paper we propose: (1) the use of discriminant analysis as a means for predictive learning (data-mining techniques) aiming at selecting metaheuristic algorithms and (2) the use of a metric for improving the selection of the algorithms that best solve a given instance of the Asymmetric Traveling Salesman Problem (ATSP). The only metric that had existed so far to determine the best algorithm for solving an ATSP instance is based on the number of cities; nevertheless, it is not sufficiently adequate for discriminating the best algorithm for solving an ATSP instance, thus the necessity for devising a new metric through the use of data-mining techniques.},
keywords = {Algorithms, chapters},
pubstate = {published},
tppubtype = {inbook}
}
In this paper we propose: (1) the use of discriminant analysis as a means for predictive learning (data-mining techniques) aiming at selecting metaheuristic algorithms and (2) the use of a metric for improving the selection of the algorithms that best solve a given instance of the Asymmetric Traveling Salesman Problem (ATSP). The only metric that had existed so far to determine the best algorithm for solving an ATSP instance is based on the number of cities; nevertheless, it is not sufficiently adequate for discriminating the best algorithm for solving an ATSP instance, thus the necessity for devising a new metric through the use of data-mining techniques. |