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Comparing and Contrasting Differential Evolution (DE) and Covariance Matrix Adaptation Evolution Strategies

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Title: Comparing and Contrasting Differential Evolution (DE) and Covariance Matrix Adaptation Evolution Strategies
Author: Opawale, Samuel
Department: School of Computer Science
Program: Computer Science
Advisor: Wineberg, Mark
Abstract: Evolutionary algorithms (EA) comprises population based algorithms that uses biologically inspired operators for optimization. DE and CMAES/IPOP are two powerful forms of EA that act on real numbers in order to provide solutions to multidimensional problems. Previously, researchers have tried to compare these two algorithms head-to-head, but no attempt has been made to compare and contrast the underlying mechanisms of these algorithms in order to better understand their effects and functionalities. The selection operator for CMA-ES was modified to make it more DElike by adding elitism selection instead of (μ, λ)). A new selection operator,here, was added to ES. We noticed an improvement with IPOP when here and elitism were used singly. In combination, the effect becomes remarkable, producing often a several orders of magnitude improvement in convergence time. One function, Levy, cause IPOP to stall when elitism was added. The reason for this is currently unknown.
URI: http://hdl.handle.net/10214/13036
Date: 2018-05


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