Identifying top-k influential nodes in social networks: a discrete hybrid optimizer by integrating butterfly optimization algorithm with differential evolution

doi:10.1007/s11227-024-06215-5

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	Identifying top-k influential nodes in social networks: a discrete hybrid optimizer by integrating butterfly optimization algorithm with differential evolution
	Tang, Jianxin 1; Zhu, Hongyu 1; Han, Lihong2 ; Song, Shihui 1
	2024-05-28
在线发表日期	2024-05
发表期刊	JOURNAL OF SUPERCOMPUTING
卷号	80 期号:13 页码:19624-19668
摘要	The most challenge of influence maximization (IM) is to locate a finite set of influencers while maximizing the influence dissemination in a social network. Due to the increasingly widespread and complex application scenarios of IM problem, how to solve the problem effectively remains as a prominent research hotspot. However, most of the existing IM algorithms tend to prioritize either lightweight computational time or solution accuracy, which are hard to be acquired simultaneously. Therefore, considering the trade-off between efficiency and effectiveness, a novel discrete hybrid optimizer by integrating butterfly optimization algorithm (BOA) with differential evolution (DE), named DBOA-DE, is proposed in this paper. An adaptive probability is designed to guide the two operations in the hybrid optimizer, where BOA shows excellent exploratory characteristics by simulating the behavior of butterfly swarms, while DE performs local exploitation through mutation and crossover procedures. Furthermore, in expectation of enhancing the solution accuracy, an improved local search policy is conceived to avoid DBOA-DE from falling into local optimum. Extensive experiments on six real-world social networks show that DBOA-DE outperforms baseline algorithms on influence propagation while maintaining acceptable efficiency, which validate the promising effectiveness and efficiency of the proposed algorithm for IM problems.
关键词	Social networks Influence maximization Discrete hybrid optimizer Butterfly optimization algorithm Differential evolution
DOI	10.1007/s11227-024-06215-5
收录类别	SCIE ; EI
ISSN	0920-8542
语种	英语
WOS研究方向	Computer Science ; Engineering
WOS类目	Computer Science, Hardware & Architecture ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic
WOS记录号	WOS:001234290500004
出版者	SPRINGER
EI入藏号	20242216188568
EI主题词	Efficiency
EI分类号	723 Computer Software, Data Handling and Applications ; 913.1 Production Engineering ; 921.5 Optimization Techniques ; 971 Social Sciences
原始文献类型	Article ; Early Access
EISSN	1573-0484
引用统计	被引频次：1[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.lzufe.edu.cn/handle/39EH0E1M/36243
专题	图书馆
通讯作者	Tang, Jianxin
作者单位	1.Lanzhou Univ Technol, Sch Comp & Commun, Lanzhou 730050, Peoples R China; 2.Lanzhou Univ Finance & Econ, Sch Stat, Lanzhou 730020, Peoples R China
推荐引用方式 GB/T 7714	Tang, Jianxin,Zhu, Hongyu,Han, Lihong,et al. Identifying top-k influential nodes in social networks: a discrete hybrid optimizer by integrating butterfly optimization algorithm with differential evolution[J]. JOURNAL OF SUPERCOMPUTING,2024,80(13):19624-19668.
APA	Tang, Jianxin,Zhu, Hongyu,Han, Lihong,&Song, Shihui.(2024).Identifying top-k influential nodes in social networks: a discrete hybrid optimizer by integrating butterfly optimization algorithm with differential evolution.JOURNAL OF SUPERCOMPUTING,80(13),19624-19668.
MLA	Tang, Jianxin,et al."Identifying top-k influential nodes in social networks: a discrete hybrid optimizer by integrating butterfly optimization algorithm with differential evolution".JOURNAL OF SUPERCOMPUTING 80.13(2024):19624-19668.