A frequency and two-hop configuration checking-driven local search algorithm for the minimum weakly connected dominating set problem

被引:0
作者
Li R. [1 ,3 ,4 ]
He J. [1 ]
Lin C. [1 ]
Liu Y. [1 ]
Hu S. [2 ]
Yin M. [2 ]
机构
[1] Jilin University of Finance and Economics, Changchun
[2] Northeast Normal University, Changchun
[3] Business Big Data Research Center of Jilin Province, Changchun
[4] Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun
基金
中国国家自然科学基金;
关键词
Combinatorial optimization; Local search; Minimum weakly connected dominating set problem; Score functions;
D O I
10.1007/s00521-024-09665-3
中图分类号
学科分类号
摘要
The minimum weakly connected dominating set problem is a typical NP-hard problem with a wide range of applications. To solve this problem, we propose a frequency property and two-hop configuration checking strategy-driven local search algorithm (FCC2LS). In this algorithm, we first propose a lock-vertex-based initial solution construction procedure. This procedure guarantees that certain vertices, which must be included in the optimal solution, are added to the solution. Second, we propose a two-hop configuration checking strategy and a frequency property. The two-hop configuration checking strategy is a new variant of the original configuration checking strategy, which prohibits vertices with unchanged configuration from being added to the candidate solution. The frequency property is used to record the number of times for each vertex is added to the solution, which can increase the diversity of selected vertices. Third, we combine two scoring functions, Dscore and Nscore, with the above strategies and propose effective vertex selection methods to help the algorithm select suitable vertices to add into or remove from the candidate solutions. Finally, we evaluate the proposed algorithm FCC2LS with four state-of-the-art algorithms on four groups of benchmark instances. Experimental results show that our algorithm performs better on four classical benchmark instances. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.
引用
收藏
页码:13833 / 13852
页数:19
相关论文
共 31 条
[1]  
Dunbar J., Grossman J., Hattingh J., Hedetniemi S., McRae A., On weakly connected domination in graphs, Discrete Math, 167-168, pp. 261-269, (1997)
[2]  
Pathan A., Hong C., Weakly connected dominating set-based secure clustering and operation in distributed sensor networks, Int J Commun Netw Distrib Syst, 3, 2, (2009)
[3]  
Du H., Wu W., Shan S., Kim D., Lee W., Constructing weakly connected dominating set for secure clustering in distributed sensor network, J Comb Optim, 23, 2, pp. 301-307, (2010)
[4]  
Bo H., Jia W., Clustering wireless ad hoc networks with weakly connected dominating set, J Parallel Distrib Comput, 67, 6, pp. 727-737, (2007)
[5]  
Li K., Leu J., Weakly connected dominating set-assisted ant-based routing protocol for wireless ad-hoc networks, Comput Electr Eng, 48, pp. 62-76, (2015)
[6]  
Xu Z., Wang J., Srimani P.K., Distributed fault tolerant computation of weakly connected dominating set in ad hoc networks, J Supercomput, 53, 1, pp. 182-195, (2009)
[7]  
Chen Y., Liestman A., Approximating minimum size weakly-connected dominating sets for clustering mobile ad hoc networks, In: Third ACM International Symposium on Mobile Ad Hoc Networking and Computing, (2002)
[8]  
Dubhashi D., Mei A., Panconesi A., Radhakrishnan J., Srinivasan A., Fast distributed algorithms for (weakly) connected dominating sets and linear-size skeletons, J Comput Syst Sci, 71, 4, pp. 467-479, (2005)
[9]  
Ding Y., Wang J.Z., Srimani P.K., A linear time self-stabilizing algorithm for minimal weakly connected dominating sets, Int J Parallel Prog, 44, 1, pp. 151-162, (2014)
[10]  
Niu D., Yin M., ) A self-stabilizing memetic algorithm for minimum weakly connected dominating set problems. In the 2nd international workshop on heuristic search in industry (HSI), Conjunction with the 31St International Joint Conference on Artificial Intelligence and the 25Th European Conference on Artificial Intelligence (IJCAI-ECAI, (2022)