.png){kind=icon}
返回
A rough set method for the unicost set covering problem
.png){kind=icon}
PRE
AI
DOI：10.1007/s13042-015-0365-2.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
In this paper, we aim to provide a rough set method to deal with a class of set covering problem called the unicost set covering problem, which is a well-known problem in binary optimization. Firstly, by constructing a Multi-Relation Granular Computing (GrC) model of a given unicost set covering problem, the problem can be equivalently converted to the knowledge reduction problem in rough set theory. Thus, various kinds of efficient knowledge reduction methods in rough set theory can be used to solve the unicost set covering problem. Secondly, a commonly used reduction algorithm based on information entropy is proposed to compute a local minimum of the unicost set covering problem. Finally, the feasibility and efficiency of the proposed algorithm is examined by an example.
Keyword:
Unicost set covering problem
Rough set
Granular computing
Local minimum
Knowledge reduction
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:
2.7
论文数:
3.2K
被引数:
5.6K
机构
引用论文
.png){kind=icon}
查看更多内容