Improving the performance of stochastic local search for maximum vertex weight clique problem using programming by optimization

doi:10.1016/j.eswa.2022.118913

	Improving the performance of stochastic local search for maximum vertex weight clique problem using programming by optimization
	Chu, Yi 1; Luo, Chuan 2; Hoos, Holger H.3; You, Haihang 4,5
	2023-03-01
发表期刊	EXPERT SYSTEMS WITH APPLICATIONS
ISSN	0957-4174
卷号	213 页码:13
摘要	The maximum vertex weight clique problem (MVWCP) is an important generalization of the maximum clique problem (MCP) that has a wide range of real-world applications. In situations where rigorous guarantees regarding the optimality of solutions are not required, MVWCP is usually solved using stochastic local search (SLS) algorithms, which also define the state of the art for solving this problem. However, there is no single SLS algorithm that gives the best performance across all classes of MVWCP instances, and it is challenging to effectively identify the most suitable algorithm for each class of MVWCP instances. In this work, we follow the paradigm of Programming by Optimization (PbO) to develop a new, flexible and highly parametric SLS framework for solving MVWCP, combining, for the first time, a broad range of effective heuristic mechanisms. By automatically configuring this PbO-MWC framework, we achieve substantial advances in the state of the art in solving MVWCP over a broad range of prominent benchmarks, including two derived from real-world applications in transplantation medicine (kidney exchange) and assessment of research excellence.
关键词	Maximum clique problem Stochastic local search Programming by optimization
DOI	10.1016/j.eswa.2022.118913
收录类别	SCI
语种	英语
资助项目	National Key Research and Development Program of China[2017YFB0202502] ; National Natural Science Foundation of China[62202025] ; National Natural Science Foundation of China[41930110]
WOS研究方向	Computer Science ; Engineering ; Operations Research & Management Science
WOS类目	Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic ; Operations Research & Management Science
WOS记录号	WOS:000886068600008
出版者	PERGAMON-ELSEVIER SCIENCE LTD
引用统计	被引频次：2[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/20298
专题	中国科学院计算技术研究所期刊论文
通讯作者	Luo, Chuan
作者单位	1.Chinese Acad Sci, Inst Software, State Key Lab Comp Sci, Beijing, Peoples R China 2.Beihang Univ, Sch Software, Beijing, Peoples R China 3.Leiden Univ, Leiden Inst Adv Comp Sci, Leiden, Netherlands 4.Chinese Acad Sci, Inst Comp Technol, State Key Lab Comp Architecture, Beijing, Peoples R China 5.Zhongguancun Lab, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Chu, Yi,Luo, Chuan,Hoos, Holger H.,et al. Improving the performance of stochastic local search for maximum vertex weight clique problem using programming by optimization[J]. EXPERT SYSTEMS WITH APPLICATIONS,2023,213:13.
APA	Chu, Yi,Luo, Chuan,Hoos, Holger H.,&You, Haihang.(2023).Improving the performance of stochastic local search for maximum vertex weight clique problem using programming by optimization.EXPERT SYSTEMS WITH APPLICATIONS,213,13.
MLA	Chu, Yi,et al."Improving the performance of stochastic local search for maximum vertex weight clique problem using programming by optimization".EXPERT SYSTEMS WITH APPLICATIONS 213(2023):13.