函数优化的改进差分进化

Q1 Social Sciences HumanMachine Communication Journal Pub Date : 2010-04-24 DOI:10.1109/MVHI.2010.146
Zhigang Zhou
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引用次数: 0

摘要

为了提高差分进化算法的性能,本文提出了一种改进的差分进化算法,该算法采用了一种新的变异算子,称为MPTDE算法。MPTDE的主要思想是对每个个体进行突变,并在当前个体和突变个体之间选择一个更适合的个体作为新的当前个体。为了验证MPTDE的性能,我们在十个知名的基准函数上进行了测试。实验结果表明,MPTDE在大多数测试函数上都优于DE。
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Improved Differential Evolution for Function Optimization
This paper presents an improved differential evolution (DE) algorithm to enhance the performance of DE. The proposed approach is called MPTDE which employs a novel mutation operator. The main idea of MPTDE is to conduct a mutation on each individual and select a fitter one between the current one and the mutated one as the new current individual. In order to verify the performance of MPTDE, we test it on ten well-known benchmark functions. The experimental results show that MPTDE outperforms DE on majority of test functions.
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CiteScore
10.00
自引率
0.00%
发文量
10
审稿时长
8 weeks
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