Abstract
During the last decades, energy consumption has become a topic of interest for algorithm designers, particularly when devoted to networked devices and mainly when handheld ones are involved. Moreover energy consumption has become a matter of paramount importance in nowadays environmentally conscious society. Although a number of studies are already available, not many have focused on Evolutionary Algorithms (EAs). Moreover, no previous attempt has been performed for modeling energy consumption behavior of EAs considering different hardware platforms. This paper thus aims at not only analyzing the influence of the main EA parameters in their energy related behavior, but also tries for the first time to develop a model that allows researchers to know how the algorithm will behave in a number of hardware devices. We focus on a specific member of the EA family, namely Genetic Programming (GP), and consider several devices when employed as the underlying hardware platform. We apply a Fuzzy Rules Based System to build the model that allows then to predict energy required to find a solution, given a previously chosen hardware device and a set of parameters for the algorithm.
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References
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Acknowledgements
We acknowledge support from Spanish Ministry of Economy and Competitiveness and European Regional Development Fund (FEDER) under project EphemeCH (TIN2014-56494-C4-{1,2,3}-P), and Junta de Extremadura FEDER, project GR15068.
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Díaz Álvarez, J., Chávez de La O, F., García Martínez, J.Á., Castillo Valdivieso, P.Á., de Vega, F.F. (2017). Estimating Energy Consumption in Evolutionary Algorithms by Means of FRBS. In: Oliveira, E., Gama, J., Vale, Z., Lopes Cardoso, H. (eds) Progress in Artificial Intelligence. EPIA 2017. Lecture Notes in Computer Science(), vol 10423. Springer, Cham. https://doi.org/10.1007/978-3-319-65340-2_19
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