Abstract
This paper investigates the mutation rates of a Genetic Algorithm (GA) with the sandpile mutation. This operator, which was specifically designed for non-stationary (or dynamic) optimization problems, relies on a Self-Organized Criticality system called sandpile to self-adapt the mutation intensity during the run. The behaviour of the operator depends on the state of the sandpile and on the fitness values of the population. Therefore, it has been argued that the mutation distribution may depend on to the severity and frequency of changes and on the type of stationary function that is chosen as a base-function for the dynamic problems. An experimental setup is proposed for investigating these issues. The results show that, at least under the proposed framework, a GA with the sandpile mutation self-adapts the mutation rates to the dynamics of the problem and to the characteristics of the base-function.
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Fernandes, C.M., Laredo, J.L.J., Mora, A.M., Rosa, A.C., Merelo, J.J. (2011). A Study on the Mutation Rates of a Genetic Algorithm Interacting with a Sandpile. In: Di Chio, C., et al. Applications of Evolutionary Computation. EvoApplications 2011. Lecture Notes in Computer Science, vol 6624. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20525-5_4
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DOI: https://doi.org/10.1007/978-3-642-20525-5_4
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