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http://bura.brunel.ac.uk/handle/2438/5860
Title: | Evolutionary programming with q-Gaussian mutation for dynamic optimization problems |
Authors: | Tinos, R Yang, S |
Keywords: | Anisotropic magnetoresistance;Biological cells;Dynamic programming;Entropy;Gaussian distribution;Genetic mutations;Genetic programming;Probability distribution;Shape control;Testing |
Issue Date: | 2008 |
Publisher: | IEEE |
Citation: | The 2008 IEEE Congress on Evolutionary Computation, Hong Kong: 1823 - 1830, 01 - 06 Jun 2008 |
Abstract: | The use of evolutionary programming algorithms with self-adaptation of the mutation distribution for dynamic optimization problems is investigated in this paper. In the proposed method, the q-Gaussian distribution is employed to generate new candidate solutions by mutation. A real parameter q, which defines the shape of the distribution, is encoded in the chromosome of individuals and is allowed to evolve. Algorithms with self-adapted mutation generated from isotropic and anisotropic distributions are presented. In the experimental study, the q-Gaussian mutation is compared to Gaussian and Cauchy mutation on three dynamic optimization problems. |
Description: | This article is posted here with permission from IEEE - Copyright @ 2008 IEEE |
URI: | http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4631036 http://bura.brunel.ac.uk/handle/2438/5860 |
DOI: | http://dx.doi.org/10.1109/CEC.2008.4631036 |
ISBN: | 978-1-4244-1822-0 |
Appears in Collections: | Publications Computer Science Dept of Computer Science Research Papers |
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