DocumentCode :
1446007
Title :
Differential Evolution With Neighborhood Mutation for Multimodal Optimization
Author :
Qu, B.Y. ; Suganthan, P.N. ; Liang, J.J.
Author_Institution :
Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ., Singapore, Singapore
Volume :
16
Issue :
5
fYear :
2012
Firstpage :
601
Lastpage :
614
Abstract :
In this paper, a neighborhood mutation strategy is proposed and integrated with various niching differential evolution (DE) algorithms to solve multimodal optimization problems. Although variants of DE are highly effective in locating a single global optimum, no DE variant performs competitively when solving multi-optima problems. In the proposed neighborhood based differential evolution, the mutation is performed within each Euclidean neighborhood. The neighborhood mutation is able to maintain the multiple optima found during the evolution and evolve toward the respective global/local optimum. To test the performance of the proposed neighborhood mutation DE, a total of 29 problem instances are used. The proposed algorithms are compared with a number of state-of-the-art multimodal optimization approaches and the experimental results suggest that although the idea of neighborhood mutation is simple, it is able to provide better and more consistent performance over the state-of-the-art multimodal algorithms. In addition, a comparative survey on niching algorithms and their applications are also presented.
Keywords :
evolutionary computation; DE algorithms; multimodal optimization problems; neighborhood based differential evolution algorithm; neighborhood mutation; niching algorithms; Algorithm design and analysis; Euclidean distance; Evolutionary computation; Genetic algorithms; Optimization; Topology; Vectors; Crowding; differential evolution; multimodal optimization; neighborhood mutation; niching algorithm; sharing; speciation;
fLanguage :
English
Journal_Title :
Evolutionary Computation, IEEE Transactions on
Publisher :
ieee
ISSN :
1089-778X
Type :
jour
DOI :
10.1109/TEVC.2011.2161873
Filename :
6151116
Link To Document :
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