File Entry: A New Hybrid Firefly Algorithm for Complex and Nonlinear Problem

Created: 2012-05-11 01:44:17      Last updated: 2012-05-11 01:44:18
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Version created on: 2012-05-11 01:44:17

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 Global optimization methods play an important role to solve many

real-world problems. However, the implementation of single methods is
excessively preventive for high dimensionality and nonlinear problems, especially
in term of the accuracy of finding best solutions and convergence speed
performance. In recent years, hybrid optimization methods have shown potential
achievements to overcome such challenges. In this paper, a new hybrid
optimization method called Hybrid Evolutionary Firefly Algorithm (HEFA) is
proposed. The method combines the standard Firefly Algorithm (FA) with the
evolutionary operations of Differential Evolution (DE) method to improve the
searching accuracy and information sharing among the fireflies. The HEFA
method is used to estimate the parameters in a complex and nonlinear biological
model to address its effectiveness in high dimensional and nonlinear problem.
Experimental results showed that the accuracy of finding the best solution and
convergence speed performance of the proposed method is significantly better
compared to those achieved by the existing methods.

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