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| Differential Evolution Algorithm Based on Coupling and Coordinating Population State Assessment |
| FENG Quanxi1,2, JIN Peiyuan1, CEN Jianmin1, AI Wu1,2, LIN Bin1,2 |
1. College of Science, Guilin University of Technology, Guilin 541004;
2. Guangxi Colleges and Universities Key Laboratory of Applied Statistics, Guilin University of Technology, Guilin 541004 |
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Abstract Differential evolution is a global stochastic search algorithm based on the differences between individuals within a population. The mutation operator is an important component of the differential evolution algorithm, and different mutation operators are suitable for different population distributions. To effectively identify the evolutionary state of the population, a differential evolution algorithm based on coupling and coordinating population state assessment(CCPDE) is proposed. The evolutionary state of the population in the iteration process is evaluated by calculating the coupling coordination degree between four different levels of fitness values and individual distances. The population is classified based on the evaluation results into three evolutionary states: search, balance and convergence, and corresponding mutation operator pools are constructed for different evolutionary states. In addition, the convergence speed of CCPDE is accelerated by adaptive adjustment of the Powell method. Numerical experiments on CEC2017 test functions show the effectiveness of CCPDE.
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Received: 27 March 2023
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| Fund:National Natural Science Foundation of China(No.62166015,62166013) |
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Corresponding Authors:
LIN Bin, Ph.D. candidate, associate professor. His research interests include computer vision.
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| About author:: FENG Quanxi, Ph.D., professor. His research interests include intelligent computing, machine learning and its applications.JIN Peiyuan, master student. Her research interests include intelligent computing.CEN Jianming, master student. His research interests include intelligent computing.AI Wu, Ph.D., associate professor. His research interests include machine learning and its applications. |
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2023, Vol. 36 
