ISCAS OpenIR  > 基础软件与系统重点实验室
local search with edge weighting and configuration checking heuristics for minimum vertex cover
Cai Shaowei; Su Kaile; Sattar Abdul
2011
SourceArtificial Intelligence
Pages1672-1696
Indexed Typeei
ISSN43702
Department(1) Key laboratory of High Confidence Software Technologies (Peking University), Ministry of Education, Beijing, China; (2) Institute for Integrated and Intelligent Systems, Griffith University, Brisbane, Australia; (3) State Key Laboratory of Computer Science, Institute of Software, Chinese Academy of Sciences, Beijing, China; (4) ATOMIC Project, Queensland Research Lab, NICTA, Australia
English AbstractThe Minimum Vertex Cover (MVC) problem is a well-known combinatorial optimization problem of great importance in theory and applications. In recent years, local search has been shown to be an effective and promising approach to solve hard problems, such as MVC. In this paper, we introduce two new local search algorithms for MVC, called EWLS (Edge Weighting Local Search) and EWCC (Edge Weighting Configuration Checking). The first algorithm EWLS is an iterated local search algorithm that works with a partial vertex cover, and utilizes an edge weighting scheme which updates edge weights when getting stuck in local optima. Nevertheless, EWLS has an instance-dependent parameter. Further, we propose a strategy called Configuration Checking for handling the cycling problem in local search. This is used in designing a more efficient algorithm that has no instance-dependent parameters, which is referred to as EWCC. Unlike previous vertex-based heuristics, the configuration checking strategy considers the induced subgraph configurations when selecting a vertex to add into the current candidate solution.A detailed experimental study is carried out using the well-known DIMACS and BHOSLIB benchmarks. The experimental results conclude that EWLS and EWCC are largely competitive on DIMACS benchmarks, where they outperform other current best heuristic algorithms on most hard instances, and dominate on the hard random BHOSLIB benchmarks. Moreover, EWCC makes a significant improvement over EWLS, while both EWLS and EWCC set a new record on a twenty-year challenge instance. Further, EWCC performs quite well even on structured instances in comparison to the best exact algorithm we know. We also study the run-time behavior of EWLS and EWCC which shows interesting properties of both algorithms. © 2011 Elsevier B.V.
KeywordCombinatorial Optimization Learning Algorithms Problem Solving
Language英语
WOS IDWOS:000292222400010
Citation statistics
Content Type会议论文
URIhttp://ir.iscas.ac.cn/handle/311060/14267
Collection基础软件与系统重点实验室
Recommended Citation
GB/T 7714
Cai Shaowei,Su Kaile,Sattar Abdul. local search with edge weighting and configuration checking heuristics for minimum vertex cover[C],2011:1672-1696.
Files in This Item:
File Name/Size DocType Version Access License
local search with ed(600KB) 开放获取--Application Full Text
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Cai Shaowei]'s Articles
[Su Kaile]'s Articles
[Sattar Abdul]'s Articles
Baidu academic
Similar articles in Baidu academic
[Cai Shaowei]'s Articles
[Su Kaile]'s Articles
[Sattar Abdul]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Cai Shaowei]'s Articles
[Su Kaile]'s Articles
[Sattar Abdul]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.