| 动态种群差分进化算法研究 |
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| 引用本文： | 王占奎,郑艳玲,杜家熙.动态种群差分进化算法研究[J].苏州科技学院学报(工程技术版),2011,24(3):68-72. |
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| 作者姓名： | 王占奎 郑艳玲 杜家熙 |
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| 作者单位： | 河南科技学院机电学院,河南新乡,453003 |
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| 基金项目： | 河南省教育厅自然科学研究计划，新乡市科技发展计划项目 |
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| 摘 要： | 针对标准差分进化算法易早熟的缺点,模拟人类社会民族融合的进化历程,提出了动态种群差分进化算法(DPDE)。算法中将种群分为多个独立的子种群,子种群之间采用相互移民来进行信息交换,设置种群分裂和融合的条件来动态控制子种群个数。通过数值实验用几种典型的测试函数对DPDE的搜索性能进行了测试,实验结果表明,该算法能有效地避免早熟,具有良好的全局收敛性。
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| 关 键 词： | 动态群体 优化 差分进化算法 |
Research on Dynamic Population Differential Evolution Algorithm |
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| WANG Zhan-kui,ZHENG Yang-ling,DU Jia-xi.Research on Dynamic Population Differential Evolution Algorithm[J].Journal of University of Science and Technology of Suzhou：Engineering and Technology,2011,24(3):68-72. |
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| Authors: | WANG Zhan-kui ZHENG Yang-ling DU Jia-xi |
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| Affiliation: | WANG Zhan-kui,ZHENG Yang-ling,DU Jia-xi (Department of Mechanical and Electric Engineering,Henan Institute of Science and Technology,Xinxiang 453003,China) |
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| Abstract: | Since the standard differential evolution is easy to fall into premature convergence, the paper presented a Dynamic Population Differential Evolution Algorithm （DPDE） which was based on simulating the evolution developing history of human races. The population was divided into several subpopulations in DPDE, and the numbers of subpopulations was dynamically controlled by merging and dividing, which could enhance the searching capacity of the algorithm. Finally, three experiments were made on benchmark functions. The results show that DPDE has a good global searching capacity than DE and can avoid premature convergence. |
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| Keywords: | dynamic population optimization differential evolution algorithm |
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