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International Journal of

Recent Trends in Engineering

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International Journal of Recent Trends in Engineering (IJRTE)

ISSN 1797-9617

Volume 1, Number 5, May 2009

Issue on Mechanical Engineering

Page(s): 63-65

An Improved Differential Evolution Algorithm for Real Parameter Optimization Problems

Musrrat Ali, Millie Pant, and V. P. Singh

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Abstract

Differential Evolution (DE) is a powerful yet simple evolutionary algorithm for optimization of real valued, multi modal functions. DE is generally considered as a reliable, accurate and robust optimization technique. However, the algorithm suffers from premature convergence, slow convergence rate and large computational time for optimizing the computationally expensive objective functions. Therefore, an attempt to speed up DE is considered necessary. This paper introduces an improved differential evolution (IDE), a modification to DE that enhances the convergence rate without compromising with the solution quality. In improved differential evolution (IDE) algorithm, initial population of individual is partitioned into several sub-populations, and then DE algorithm which utilize only one set of population instead of two as in original DE, is applied to each sub-population independently. At periodic stages in evolution, the entire population is shuffled, and then points are reassigned to sub-populations. The performance of IDE on a test bed of functions is compared with original DE. It is found that IDE requires less computational effort to locate global optimal solution.

Index Terms

Differential evolution, shuffled complex evolution, optimization.

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