Genetic Algorithms for Tracking Changing Environments
Proceedings of the 5th International Conference on Genetic Algorithms
A self-organizing random immigrants genetic algorithm for dynamic optimization problems
Genetic Programming and Evolvable Machines
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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.