[1]高 尚,邱 玲,曹存根.解连续性优化问题的摸石头过河算法[J].南京师大学报(自然科学版),2015,38(01):108.
　Gao Shang,Qiu Ling,Cao Cungen.Solving Continuous Optimization Problem by WadingAcross Stream Algorithm[J].Journal of Nanjing Normal University(Natural Science Edition),2015,38(01):108.
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解连续性优化问题的摸石头过河算法()
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《南京师大学报》（自然科学版）[ISSN:1001-4616/CN:32-1239/N]

卷:
第38卷
期数:
2015年01期
页码:
108
栏目:
计算机科学
出版日期:
2015-06-30

文章信息/Info

Title:
Solving Continuous Optimization Problem by WadingAcross Stream Algorithm
作者:
高 尚1; 邱 玲2; 曹存根3
(1.江苏科技大学计算机科学与工程学院,江苏 镇江 212003)(2.人工智能四川省高校重点实验室,四川 自贡 643000)(3.中国科学院计算所智能信息处理重点实验室,北京 100190)
Author(s):
Gao Shang1; Qiu Ling2; Cao Cungen3
(1.School of Computer Science and Engineering,Jiangsu University of Science and Technology,Zhenjiang 212003,China)(2.Artificial Intelligence of Key Laboratory of Sichuan Province,Zigong 643000,China)(3.Key Lab of Intelligent Information Processing of Chinese Academy of Sciences,Institute of Computing Technology,Beijing 100190,China)
关键词:
随机优化算法; 连续空间优化; 快速随机优化算法; 摸石头过河
Keywords:
random optimization algorithm; continuous space optimization; fast random optimization algorithm; Wading across Stream Algorithm
分类号:
TP18
文献标志码:
A
摘要:
依据“摸石头过河”的思想,提出一种快速、高效的随机优化算法. 摸石头过河算法是以一个解为起点,向该起点附近邻域随机搜索若干个解,找出这些解中的最好的一个解,以此解为下次迭代的结果,然后以此点为起点,再向附近邻域随机搜索若干个解,以此类推. 解连续性优化问题时改进的方法是逐渐缩小搜索空间,对几个经典测试函数进行实验的结果表明,利用摸石头过河及其改进算法能够极大地提高收敛速度和精度.
Abstract:
According to idea of Wading across the Stream by feeling the way,a kind of fast efficient random optimization algorithm is put forward. The Wading across Stream Algorithm(WSA)acts a solution as a start point,then searches several solutions randomly near the start point,and finds the best solution of these solutions. This best solution is to take as next start point,and then several random solutions near this start point are searched,and so on. For solving continuous optimization problem,the improved Wading across Stream Algorithm shrinks the search space gradually. The experiment results of some classic benchmark functions show that the proposed optimization algorithms improve extraordinarily the convergence velocity and precision.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2014-08-20.
基金项目:人工智能四川省重点实验室开放基金(2012RYJ04)、中科院智能信息处理重点实验室开放课题(IIP2013-1).
通讯联系人:高尚,博士,教授,研究方向:智能计算研究. E-mail:gaoshang@sohu. Com
更新日期/Last Update: 2015-03-30