Abstract
This paper presents a method for accelerating the evaluation of individuals in Grammatical Evolution. The method is applied for identification and modeling problems, where, in order to obtain the fitness value of one individual, we need to compute a mathematical expression for different time events. We propose to evaluate all necessary values of each individual using only one mathematical Java code. For this purpose we take profit of the flexibility of grammars, which allows us to generate Java compilable expressions. We test the methodology with a real problem: modeling glucose level on diabetic patients. Experiments confirms that our approach (compilable phenotypes) can get up to 300x reductions in execution time.
J.M. Colmenar—Support from Spanish Government Grant TIN2014-54806-R is acknowledged by ABSyS group.
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Colmenar, J.M. et al. (2016). Compilable Phenotypes: Speeding-Up the Evaluation of Glucose Models in Grammatical Evolution. In: Squillero, G., Burelli, P. (eds) Applications of Evolutionary Computation. EvoApplications 2016. Lecture Notes in Computer Science(), vol 9598. Springer, Cham. https://doi.org/10.1007/978-3-319-31153-1_9
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DOI: https://doi.org/10.1007/978-3-319-31153-1_9
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