Control of the number of random imigrants in genetic algorithms for protein structure prediction
Vinicius Tragante, Renato Tinós · 2009
In the Genetic Algorithm with the standard random immigrants approach, a fixed number of individuals of the current population are replaced by random individuals in every generation. The rate of replaced individuals is defined a priori, and has a great impact on the performance of the algorithm. In this paper we present a new strategy to control the number of random immigrants in Genetic Algorithms applied to the protein structure prediction problem. Instead of using a fixed number of new individuals per generation, the proposed approach increases or decreases the number of new individuals to be inserted in the generation according to a self-organizing process. Results show that with the algorithm can determine the number of replaced individuals per generation in a self-organized way.