2016
|
1. | Bernábe-Loranca, Beatríz; Ruíz-Vanoye, Jorge A.; González-Velázquez, Rogelio; Analco, Martín Estrada; López, Abraham Sánchez; Ochoa-Zezzatti, Alberto; Martínez-Guzman, Gerardo; Díaz, Mario Bustillo An approximation method for the P-median problem: A bioinspired tabu search and variable neighborhood search partitioning approach Journal Article In: International Journal of Hybrid Intelligent Systems, vol. 13, no. 2, pp. 87-98, 2016, ISSN: 1448-5869. @article{journ201812294,
title = {An approximation method for the P-median problem: A bioinspired tabu search and variable neighborhood search partitioning approach},
author = {Beatríz Bernábe-Loranca and Jorge A. Ruíz-Vanoye and Rogelio González-Velázquez and Martín Estrada Analco and Abraham Sánchez López and Alberto Ochoa-Zezzatti and Gerardo Martínez-Guzman and Mario Bustillo Díaz
},
doi = {10.3233/HIS-160227},
issn = {1448-5869},
year = {2016},
date = {2016-08-01},
journal = {International Journal of Hybrid Intelligent Systems},
volume = {13},
number = {2},
pages = {87-98},
keywords = {Algorithms},
pubstate = {published},
tppubtype = {article}
}
|
2010
|
2. | 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. |
2008
|
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. |