Targeted Mutation: A Novel Mutation Strategy for Differential Evolution

被引:0
作者
Zheng, Weijie [1 ,2 ]
Fu, Haohuan [1 ]
Yang, Guangwen [1 ,2 ]
机构
[1] Tsinghua Univ, Ctr Earth Syst Sci, Key Lab Earth Syst Modeling, Minist Educ, Beijing 100084, Peoples R China
[2] Tsinghua Univ, Dept Comp Sci & Technol, Beijing 100084, Peoples R China
来源
2015 IEEE 27TH INTERNATIONAL CONFERENCE ON TOOLS WITH ARTIFICIAL INTELLIGENCE (ICTAI 2015) | 2015年
关键词
Differential evolution (DE); mutation operator; evolutionary computhlg; numerical optimization;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Differential Evolution (DE) has been shown as an effective, efficient and robust evolutionary computing algorithm. The main force to generate promising offspring is the mutation operator. Usually, two randoudy selected vectors are used to generate the differential vector, which maintains the large diversity of mutant directions and ensures the possibility to find global opthna. However, strong randomness also leads to the ineffective searching and slow convergence speed. A proper degree of certainty in differential vector will help the population evolve efficiently. This paper proposes a novel mutation strategy called Targeted Mutation that takes the determined target vector as the starting point of the differential vector and maintains the randomness of the ending point, which makes a better trade-off between the certainty and randomness in the differential vector. Besides, Targeted Mutation adopts the best vector as the base vector. The extensive experiments of comparison with two popular mutation operators on 20 benchmark functions demonstrate the competitive performance of our proposed targeted mutation scheme. Our method achieves better or equivalent performance over 70% of total benchmarks against the other two methods. 17 out of 20 function results can get further improved when roughly tuning parameters on each function, showing the potential ability to get even better results. In addition, an integrated evaluation scoring scheme is designed to provide a more concrete demonstration of the overall performance of different approaches, and our method gains the highest score.
引用
收藏
页码:286 / 293
页数:8
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