.png){kind=icon}
返回
Improving local search algorithms for clique relaxation problems via group driven initialization
.png){kind=icon}
PRE
AI
DOI：10.1007/s11704-024-40238-8.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Clique relaxation problems are important extension versions of the maximum clique problem with extensive real-world applications. Although lots of studies focus on designing local search algorithms for solving these problems, almost all state-of-the-art local search algorithms adopt a common general initialization method. This paper develops a general group driven initialization method for clique relaxation problems. The proposed method uses two kinds of ways to divide vertices into some subgroups by using the useful information of the search procedure and the structure information of a given instance and then constructs a good initial solution by considering the generated group information. We apply the proposed initialization method to two clique relaxation problems. Experimental results demonstrate that the proposed initialization method clearly improves the performance of state-of-the-art algorithms for the clique relaxation problems.
Keyword:
combinatorial optimization
clique relaxation problems
group driven initialization
local search
group information
期刊
IF:
4.6
论文数:
1.6K
被引数:
2.8K
机构
引用论文
An improved master-apprentice evolutionary algorithm for minimum independent dominating set problem
.png){kind=icon}
PREAI
分享收藏分享收藏
查看更多内容