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  2013, Vol. 26 Issue (8): 711-721    DOI:
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Adaptive Multiple Strategy Differential Evolution Algorithmwith Guiding Scheme of Pbest
XIANG Wan-Li1, 2, MA Shou-Feng1, AN Mei-Qing2
1. Institute of Systems Engineering, Tianjin University, Tianjin 300072
2.School of Traffic and Transportation, Lanzhou Jiaotong University, Lanzhou 730070

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Abstract  

To improve the convergence performance of differential evolution algorithm, an adaptive multiple strategy differential evolution algorithm (AMSDE) with guiding scheme of Pbest is proposed. The library of control parameters of the crossover probability, the library of scale parameters of the mutation and the library of the differential mutation strategy are designed in AMSDE. Thereinto, the crossover probability is generated by Logistic chaotic systems, the scale parameter is produced by means of a linear changing scheme, and the library of differential mutation strategy consists of six widely used differential mutation strategies. Subsequently, the framework of AMSDE is given. Finally, simulation results on 25 benchmark test functions demonstrate that AMSDE achieves better convergence precision and a higher convergence speed. And AMSDE outperforms the two state-of-the-art variants of differential evolution algorithms, JADE and CoDE.

Key wordsDifferential Evolution Algorithm      Logistic Chaotic System      Guiding Scheme of Pbest      Multiple Differential Mutation Strategy      Shifted and Rotated Functions     
Received: 20 July 2012     
ZTFLH: TP301.6  
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XIANG Wan-Li
MA Shou-Feng
AN Mei-Qing
Cite this article:   
XIANG Wan-Li,MA Shou-Feng,AN Mei-Qing. Adaptive Multiple Strategy Differential Evolution Algorithmwith Guiding Scheme of Pbest[J]. , 2013, 26(8): 711-721.
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http://manu46.magtech.com.cn/Jweb_prai/EN/      OR     http://manu46.magtech.com.cn/Jweb_prai/EN/Y2013/V26/I8/711
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