| 自适应权重差分进化算法 |
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| 引用本文： | 王建芹,高兴宝. 自适应权重差分进化算法[J]. 陕西科技大学学报, 2012, 0(4): 125-128 |
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| 作者姓名： | 王建芹 高兴宝 |
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| 作者单位： | 陕西师范大学数学与信息科学学院 |
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| 基金项目： | 国家自然科学基金项目(10902062);中央高校基本科研业务费专项基金资助(GK201001002) |
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| 摘 要： | 针对使用不同中间向量遗传策略（学习策略）的差分进化算法所表现出的性能不同,提出一种改进的差分进化算法,对已有的两种遗传策略引入自适应权重,设计了一个新的中间向量遗传策略.通过对基准函数进行测试,结果表明新算法避免了早熟收敛,寻优性能较好,收敛速度较快,具有一定的有效性.
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| 关 键 词： | 差分进化算法 自适应权重 函数优化 |
Adaptive-weight differential evolution algorithm |
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| WANG Jian-qin,GAO Xing-bao. Adaptive-weight differential evolution algorithm[J]. Journal of Shaanxi University of Science & Technology(Natural Science Edition), 2012, 0(4): 125-128 |
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| Authors: | WANG Jian-qin GAO Xing-bao |
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| Affiliation: | (College of Mathematics and Information Science,Shaanxi Normal University,Xi′an 710062,China) |
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| Abstract: | In this paper,an improved differential evolution algorithm is proposed,due to the performance shown by differential evolution algorithms using different learning strategies are different.In the new algorithm,we design a new learning strategy of intermediate vector by introducing adaptive weights to two learning strategies.The results of tests on benchmark functions show that the new algorithm can avoid premature convergence,improve the convergence speed and has higher searching ability,therefore,it illustrates the effectiveness of the new algorithm. |
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| Keywords: | differential evolution algorithm adaptive weight functional optimization |
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