| 改进自适应变空间差分进化算法 |
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| 引用本文： | 姚峰,杨卫东,张明,李仲德.改进自适应变空间差分进化算法[J].控制理论与应用,2010,27(1):32-38. |
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| 作者姓名： | 姚峰 杨卫东 张明 李仲德 |
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| 作者单位： | 1. 北京科技大学信息工程学院,北京,100083
2. 北京科技大学钢铁流程先进控制教育部重点实验室,北京,100083 |
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| 基金项目： | 国家高技术专项项目(2005–1). |
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| 摘 要： | 在基本差分进化算法的基础上融入自适应变空间思想,提出自适应变空间差分进化算法,在进化代数达到预设周期整数倍时,按变空间算法自动扩展或收缩搜索空间,实现了自动寻找合适搜索空间、提高收敛速度和精度的目的.此外为了进一步的加快收敛速度,对原变空间算法进行了改造,对其上下限的变化规则进行了修改和添加,提出了改进的变空间算法.仿真结果表明改进方法在收敛精度、速度上优于基本差分进化算法和基于原变空间算法的差分进化算法.最后将其应用到热连轧机精轧机组负荷分配优化计算中,为其提供了一种有效的优化手段.
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| 关 键 词： | 改进自适应变空间算法 差分进化算法 热连轧机 负荷分配 |
| 收稿时间： | 2008/10/23 0:00:00 |
| 修稿时间： | 2009/4/18 0:00:00 |
Improved space-adaptive-based differential evolution algorithm |
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| YAO Feng,YANG Wei-dong,ZHANG Ming and LI Zhong-de.Improved space-adaptive-based differential evolution algorithm[J].Control Theory & Applications,2010,27(1):32-38. |
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| Authors: | YAO Feng YANG Wei-dong ZHANG Ming and LI Zhong-de |
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| Affiliation: | School of Information Engineering, University of Sciences and Technology Beijing; Key Laboratory of Advanced Control of Iron and Steel Process (Ministry of Education), University of Science and Technology Beijing,School of Information Engineering, University of Sciences and Technology Beijing; Key Laboratory of Advanced Control of Iron and Steel Process (Ministry of Education), University of Science and Technology Beijing,School of Information Engineering, University of Sciences and Technology Beijing; Key Laboratory of Advanced Control of Iron and Steel Process (Ministry of Education), University of Science and Technology Beijing,School of Information Engineering, University of Sciences and Technology Beijing; Key Laboratory of Advanced Control of Iron and Steel Process (Ministry of Education), University of Science and Technology Beijing |
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| Abstract: | To improve the performance of differential evolution algorithm we present a differential evolution algorithm with space-adaptive idea, which expands or shrinks the search space by certain rules. It realizes the automatic search for
the suitable space and improves the convergence rate and accuracy. For further improvement of the convergence rate, the original space-adaptive algorithm is modified by revising the existing rules and adding new rules. The simulation
results show that the improved space-adaptive-based differential evolution algorithm is better than the original differential evolution algorithm in convergence rate and accuracy. This algorithm is applied to several hot strip mills for the optimal design of scheduling. |
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| Keywords: | improved space adaptive algorithm differential evolutional algorithm hot strip mills load distribution |
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