Int. J. of Wireless and Mobile Computing   »   2016 Vol.10, No.1

 

 

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Title: A new modified differential evolution for global optimisation

 

Authors: Xuemei You; Yinghong Ma; Zhiyuan Liu

 

Addresses:
School of Management Science and Engineering, Shandong Normal University, Jinan 250014, China; Key Laboratory of Intelligent Computing & Signal Processing, Ministry of Education, Anhui University, Hefei 230039, China
School of Management Science and Engineering, Shandong Normal University, Jinan 250014, China
School of Management Science and Engineering, Shandong Normal University, Jinan 250014, China

 

Abstract: Differential evolution (DE) is a population-based random optimisation algorithm, which has been used to solve benchmark functions and real-world optimisation problems. The DE has three important operators: mutation, crossover, and selection. The mutation operator in the original DE can hardly balance the exploitation and exploration of the search. In this paper, we design a new mutation operator to improve the exploitation ability of DE. Experiments are carried out on 13 classical test functions. Simulation results show that the new mutation scheme can help DE to find better solutions than three other classical DE mutation strategies.

 

Keywords: differential evolution; mutation operator; function optimisation; global optimisation; exploitation ability; simulation.

 

DOI: 10.1504/IJWMC.2016.075219

 

Int. J. of Wireless and Mobile Computing, 2016 Vol.10, No.1, pp.56 - 61

 

Submission date: 11 May 2015
Date of acceptance: 03 Jun 2015
Available online: 07 Mar 2016

 

 

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