A GPU-based implementation of the firefly algorithm for variable selection in multivariate calibration problems
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2014-12
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Several variable selection algorithms in multivariate calibration can be accelerated
using Graphics Processing Units (GPU). Among these algorithms, the Firefly
Algorithm (FA) is a recent proposed metaheuristic that may be used for variable
selection. This paper presents a GPU-based FA (FA-MLR) with multiobjective
formulation for variable selection in multivariate calibration problems and compares
it with some traditional sequential algorithms in the literature. The advantage of the
proposed implementation is demonstrated in an example involving a relatively large
number of variables. The results showed that the FA-MLR, in comparison with the
traditional algorithms is a more suitable choice and a relevant contribution for the
variable selection problem. Additionally, the results also demonstrated that the FAMLR
performed in a GPU can be five times faster than its sequential
implementation.
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PAULA, Lauro C. M. de; SOARES, Anderson S.; LIMA, Telma W.; DELBEM, Alexandre C. B.; COELHO, Clarimar J.; GALVÃO FILHO, Arlindo R. A GPU-based implementation of the firefly algorithm for variable selection in multivariate calibration problems. Plos One, San Francisco, v. 9, n. 12, p. e114145, Dec. 2014.