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...

求解多任务调度问题的免疫蚁群算法*

, PP. 73-78

Keywords: 蚁群算法,任务调度,并行分布系统,表调度算法,免疫原理

Full-Text   Cite this paper   Add to My Lib

Abstract:

提出一种免疫蚁群算法去解决具有约束关系的多任务调度问题.它采用蚁群算法来进化任务调度的优先队列,然后再使用贪婪策略把优先队列映射为一个有效的调度.为抑制早熟停滞现象,算法中使用免疫原理来保持蚁群的多样性.仿真结果表明,本算法在解的质量和算法的执行时间方面都具有较好的性能.

References

[1]  Wu M Y, Gajski D D. Hypertool: A Programming Aid for Message-Passing Systems. IEEE Trans on Parallel and Distributed Systems, 1990, 1(3): 330-343
[2]  Shi W, Zheng W M. The Balanced Dynamic Critical Path Scheduling Algorithm of Dependent Task Graphs. Chinese Journal of Computers, 2001, 24(9): 991-997 (in Chinese) (石 威,郑纬民.相关任务图的均衡动态关键路径调度算法.计算机学报, 2001, 24(9): 991-997)
[3]  Zhong Y W, Yang J G. A Genetic Algorithm for Tasks Scheduling in Parallel Multiprocessor Systems. In: Proc of the 2nd International Conference on Machine Learning and Cybernetics. Xi’an, China, 2003, Ⅲ: 1785-1790
[4]  Colorni A, Dorigo M, Maniezzo V. Distributed Optimization by Ant Colonies. In: Proc of the 1st European Conference on Artificial Life. Paris, France, 1992, 134-142
[5]  Colorni A, Dorigo M, Maniezzo V. An Investigation of Some Properties of an Ant Algorithm. In: Proc of the Parallel Problem Solving from Nature Conference. Brussels, Belgium, 1992, 509-520
[6]  Wang X F, Zhang X J, Cao X B, et al. An Improved Genetic Algorithm Based on Immune Principle. Mini-Micro Systems, 1999, 20(2): 117-120 (in Chinese) (王煦法,张显俊,曹先彬,等.一种基于免疫原理的遗传算法.小型微型计算机系统, 1999, 20(2): 117-120)
[7]  Cui X X, Li M, Fang T J. Research on Population Diversity of Multi-Objective Evolutionary Algorithms Based on Immune Principle. Pattern Recognition and Artificial Intelligence, 2001, 14(3): 291-296 (in Chinese) (崔逊学,李 淼,方廷健.基于免疫原理的多目标进化算法群体多样性研究.模式识别与人工智能, 2001, 14(3): 291-296)
[8]  Dorigo M, Maniezzo V, Colorni A. The Ant System: Optimization by a Colony of Cooperating Agents. IEEE Trans on Systems, Man, and Cybernetics-Part B: Cybernetics, 1996, 26(1): 29-41
[9]  Stutzle T, Hoos H. Improvements on the Ant System: Introducing MAX-MIN Ant System. In: Proc of the International Conference on Artificial Neural Networks and Genetic Algorithms. Heidelberg, Germany: Springer Verlag, 1997, 245-249
[10]  Bullnheimer B, Hartl R F, Strauss C. A New Rank Based Version of the Ant System: A Computational Study. Central European Journal for Operations Research and Economics, 1999, 7(1): 25-38
[11]  Nakamichi Y, Arita T. Diversity Control in Ant Colony Optimization. 2004. http://www.it.bond.edu.au/publications/02TR/02-18.pdf
[12]  Almeida V A F, Vasconcelos I M M, Arabe J N C, Menusc D A. Using Random Task Graphs to Investigate the Potential Benefits of Heterogeneity in Parallel Systems. In: Proc of the IEEE/ACM Conference on High Performance Networking and Computing. Minneapolis, USA, 1992, 683-691

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133