A Modified Differential Evolution Algorithm with Cauchy Mutation for Global Optimization

被引:2
作者
Ali, Musrrat [1 ]
Pant, Millie [1 ]
Singh, Ved Pal [1 ]
机构
[1] Indian Inst Technol Roorkee, Dept Paper Technol, Saharanpur 247001, India
来源
CONTEMPORARY COMPUTING, PROCEEDINGS | 2009年 / 40卷
关键词
Differential evolution; Cauchy mutation;
D O I
10.1007/978-3-642-03547-0_13
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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 research introduces a modified differential evolution (MDE), a modification to DE that enhances the convergence rate without Compromising with the solution quality. In Modified differential evolution (MDE) algorithm,. if an individual fails in continuation to improve its performance to a specified number of times then new point is generated using Cauchy mutation. MDE oil a test bed of functions is compared with original DE. It is found that MDE requires less computational effort to locate global optimal solution.
引用
收藏
页码:127 / 137
页数:11
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