全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...

Ant-colony-genetic algorithm with adaptive parameters based on grey prediction and normal cloud
基于灰预测和正态云的参数自适应蚁群遗传算法

Keywords: hybrid algorithm,max-min ant system(MMAS),genetic algorithm (GA),normal cloud,grey prediction
混合算法
,最大最小蚂蚁系统,遗传算法,正态云,灰预测

Full-Text   Cite this paper   Add to My Lib

Abstract:

Ant colony algorithm with positive feedback has a good capability of global convergence; while the genetic algorithm(GA) is with a fast performance in global search. A hybrid algorithm with adaptive parameters is proposed to take advantages of the above two optimization algorithm. Using the grey prediction, we obtain in the ant colony strategy the estimates of the maximum (minimum) trail limits which are controlled for avoiding the immature convergence. Meanwhile, we employ the cloud models to build a set of association rules which are used to adaptively adjust algorithm parameters by information feedback during the iterative process, thus reducing the reliance on initial parameters. Simulation results for job-shop scheduling problem(JSP) and traveling salesman problem(TSP) validate the algorithm.

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133