Compilable phenotypes: speeding-up the evaluation of glucose models in grammatical evolution


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.

European Conference on the Applications of Evolutionary Computation
J. Manuel Colmenar
J. Manuel Colmenar
Associate Professor

My research interests are focused on metaheuristics applied to optimization problems. I have worked on different combinatorial optimization problems applying trajectorial algorithms such us GRASP or VNS. Besides, I am very interested in applications of Grammatical Evolution, specifically in model and prediction domain, as alternative to machine learning approaches.