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On the selection of solutions for mutation in differential evolution |
Yong WANG1,2( ), Zhi-Zhong LIU1, Jianbin LI3, Han-Xiong LI4,5, Jiahai WANG6 |
1. School of Information Science and Engineering, Central South University, Changsha 410083, China 2. School of Computer Science and Informatics, De Montfort University, Leicester LE1 9BH, UK 3. Institute of Information Security and Big Data, Central South University, Changsha 410083, China 4. Department of Systems Engineering and EngineeringManagement, City University of Hong Kong, Hong Kong, China 5. State Key Laboratory of High Performance Complex Manufacturing, Central South University, Changsha 410083, China 6. School of Data and Computer Science, Sun Yat-sen University, Guangzhou 510006, China |
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Abstract Differential evolution (DE) is a kind of evolutionary algorithms, which is suitable for solving complex optimization problems. Mutation is a crucial step in DE that generates new solutions from old ones. It was argued and has been commonly adopted in DE that the solutions selected for mutation should have mutually different indices. This restrained condition, however, has not been verified either theoretically or empirically yet. In this paper, we empirically investigate the selection of solutions for mutation in DE. From the observation of the extensive experiments, we suggest that the restrained condition could be relaxed for some classical DE versions as well as some advanced DE variants. Moreover, relaxing the restrained condition may also be useful in designing better future DE algorithms.
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Keywords
differential evolution
mutation
the selection of solutions for mutation
evolutionary algorithms
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Corresponding Author(s):
Yong WANG
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Just Accepted Date: 19 July 2016
Online First Date: 29 June 2017
Issue Date: 23 March 2018
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