Date of Award
Master of Science (MS)
In this thesis I demonstrate a novel application of chaotic dynamics to evolutionary algorithms, specifically in population size management. Typical evolutionary algorithms require a population size to be set as a parameter, which remains constant throughout execution. I created a new algorithm that can vary the population size chaotically or periodically, and do a series of performance tests comparing static, periodic, and chaotic population control. The problems targeted in these tests are chosen from both continuous and discrete multi-dimensional domains. I find that both chaotic and static population control perform well in certain situations; my evidence suggests that periodic population control is rarely a good choice. I also present additional analysis on the effects of the population dynamics and how they relate to mean population size and variance in the performance results.
Nelson, Thomas Harrison, "Genetic Algorithms with Chaotic Population Dynamics" (2010). Computer Science Graduate Theses & Dissertations. 18.