An Improved Differential Evolution and its Application in Function Optimization Problem

Abstract:

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An Improved Differential evolution (IDE) is proposed in this paper. It has some new features: 1) using multi-parent search strategy and stochastic ranking strategy to maintain the diversity of the population; 2) a novel convex mutation to accelerate the convergence rate of the classical DE algorithm.; The algorithm of this paper is tested on 13 benchmark optimization problems with linear or/and nonlinear constraints and compared with other evolutionary algorithms. The experimental results demonstrate that the performance of IDE outperforms DE in terms of the quality of the final solution and the stability.

Info:

Periodical:

Edited by:

Yanwen Wu

Pages:

632-634

DOI:

10.4028/www.scientific.net/AMR.267.632

Citation:

J. F. Yan and C. F. Guo, "An Improved Differential Evolution and its Application in Function Optimization Problem", Advanced Materials Research, Vol. 267, pp. 632-634, 2011

Online since:

June 2011

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Price:

$35.00

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