@article{(Open Science Index):https://publications.waset.org/pdf/10004073,
	  title     = {Discriminant Analysis as a Function of Predictive Learning to Select Evolutionary Algorithms in Intelligent Transportation System},
	  author    = {Jorge A. Ruiz-Vanoye and  Ocotlán Díaz-Parra and  Alejandro Fuentes-Penna and  Daniel Vélez-Díaz and  Edith Olaco García},
	  country	= {},
	  institution	= {},
	  abstract     = {In this paper, we present the use of the discriminant analysis to select evolutionary algorithms that better solve instances of the vehicle routing problem with time windows. We use indicators as independent variables to obtain the classification criteria, and the best algorithm from the generic genetic algorithm (GA), random search (RS), steady-state genetic algorithm (SSGA), and sexual genetic algorithm (SXGA) as the dependent variable for the classification. The discriminant classification was trained with classic instances of the vehicle routing problem with time windows obtained from the Solomon benchmark. We obtained a classification of the discriminant analysis of 66.7%.
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {10},
	  number    = {3},
	  year      = {2016},
	  pages     = {566 - 573},
	  ee        = {https://publications.waset.org/pdf/10004073},
	  url   	= {https://publications.waset.org/vol/111},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 111, 2016},