.png){kind=icon}
返回
A hybrid particle Swann optimization algorithm for optimal task assignment in distributed systems
.png){kind=icon}
PRE
AI
DOI：10.1016/j.csi.2005.03.005.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
In a distributed system, a number of application tasks may need to be assigned to different processors such that the system cost is minimized and the constraints with limited resource are satisfied. Most of the existing formulations for this problem have been found to be NP-complete, and thus finding the exact solutions is computationally intractable for large-scaled problems. This paper presents a hybrid particle swarm optimization algorithm for finding the near optimal task assignment with reasonable time. The experimental results manifest that the proposed method is more effective and efficient than a genetic algorithm. Also, our method converges at a fast rate and is suited to large-scaled task assignment problems. (c) 2005 Elsevier B.V. All rights reserved.
Keyword:
task assignment problem
distributed systems
hybrid strategy
particle swarm optimization
genetic algorithm
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
C
IF:
3.1
论文数:
2.3K
被引数:
2.0K
机构
暂无机构信息
引用论文
分享收藏Diabetes is associated with increased risk for in-hospital mortality in patients with COVID-19: a systematic review and meta-analysis comprising 18,506 patients.png)
Hormones
OAAI
HormonesIF0
OAAI分享收藏Adsorption of Cu(II), Pb(II), and Cd(II) Ions from Acidic Aqueous Solutions by Diethylenetriaminepentaacetic Acid-Modified Magnetic Graphene Oxide二乙烯三胺五乙酸改性的磁性氧化石墨烯对酸性水溶液中Cu(II)，Pb(II) 和Cd(II) 离子的吸附
PREAI
分享收藏
分享收藏
查看更多内容