.png){kind=icon}
返回
Monte-Carlo randomized algorithm for minimum feedback arc set
.png){kind=icon}
PRE
AI
DOI：10.1016/j.asoc.2015.12.018.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
When we are developing information system we must, in some way, determine the development order of its subsystems. Currently, this problem is not formally solved. Therefore, to rectify this we are proposing a solution which takes the sum of weights of feedback arcs as a criteria for determining the development order, rather than some other criteria that has not come directly from information system description. For the purpose of solving this problem we have developed, analyzed, and tested, Branch and Bound algorithm and Monte-Carlo randomized algorithm which solves the problem of Information System Subsystems Development Order in polynomial time with arbitrary probability. Also, we have determined an approximation error for developed Monte-Carlo randomized algorithm. Lastly, we have proven that the problem of Information System Subsystems Development Order is NP-hard, NP-complete, and APX-hard. (C) 2015 Elsevier B.V. All rights reserved.
Keyword:
Minimum feedback arc set
Monte Carlo
Randomization
NP-hard
NP-complete
APX-hard
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
IF:
6.6
论文数:
1.4W
被引数:
4.8W
机构
引用论文
.png){kind=icon}
分享收藏分享收藏
分享收藏分享收藏
查看更多内容