一种基于灰预测理论的混合蛙跳算法

doi:10.19595/j.cnki.1000-6753.tces.160634

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Abstract To enhance the performance of shuffled frog leaping algorithm in solving optimization problems,a new model for hybrid leapfrog algorithm based on grey prediction theory was proposed.The algorithmic evolution model was adjusted to strengthen the ability to exchange the global information in the process of evolution.Then the algorithm implemented the mobile step self-adaption adjustment through introduced mobile step mutation operator.The mutation operator was controlled by the different stages of evolution and the optimal solution progress speed in the process of evolution obtained by grey prediction theory and the fuzzy control thoughts.The advantages of the improved hybrid leapfrog algorithm,such as the accuracy,convergent speed and success rate,and the feasibility of grey prediction theory in the field of algorithm improvement,is verified by comparison with the basic shuffled frog leaping algorithm and the known improved algorithm on performance through six standard test functions.Finally,the practicability of the improved algorithm is proved by applying it to 10 kV oil-immersed distribution transformer optimization design works.

Key words： Shuffled frog leaping algorithm grey prediction mutation operator optimal design

Received: 09 May 2016 Published: 18 August 2017

PACS:

TP301

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	Du Jiang
	Yuan Zhonghua
	Wang Jingqin

Cite this article:

Du Jiang,Yuan Zhonghua,Wang Jingqin. Shuffled Frog Leaping Algorithm Based on Grey Prediction Theory[J]. Transactions of China Electrotechnical Society, 2017, 32(15): 190-198.

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https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.160634 OR https://dgjsxb.ces-transaction.com/EN/Y2017/V32/I15/190

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