A new local search algorithm with greedy crossover restart for the dominating tree problem

被引:3
|
作者
Niu, Dangdang [1 ,3 ,4 ]
Liu, Bin [1 ,3 ,4 ]
Yin, Minghao [2 ]
Zhou, Yupeng [2 ]
机构
[1] Northwest A&F Univ, Coll Informat Engn, Yangling 712100, Shaanxi, Peoples R China
[2] Northeast Normal Univ, Sch Comp Sci & Informat Technol, Changchun 130117, Peoples R China
[3] Northwest A&F Univ, Shaanxi Key Lab Agr Informat Percept & Intelligent, Yangling 712100, Peoples R China
[4] Northwest A&F Univ, Key Lab Agr Internet Things, Minist Agr & Rural Affairs, Yangling 712100, Shaanxi, Peoples R China
关键词
Combinatorial optimization; Dominating tree problem; Iterated local search; Restart; Score functions; STRATEGIES;
D O I
10.1016/j.eswa.2023.120353
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The dominating tree problem (DTP), a variant of the classical minimum dominating set problem, aims to find a dominating tree of minimum costs on a given connected, undirected and edge-weighted graph. In this paper, we design an efficient local search algorithm named LSGCR_DTP to solve DTP. To this end, we propose four new strategies to make it efficient. Firstly, we design a new connecting method for non-connected dominating sets, which no longer depends on the shortest paths between each pair of vertices used in the existing DTP solvers. Secondly, we propose a new method for improving the current feasible connected dominating sets by adding some special vertices to them. Thirdly, a vertex selection strategy for balancing the connecting property and dominating property of solution is introduced. Fourthly, a new restart strategy based on greedy mechanism and crossover operation is integrated to our local search algorithm. Experimental results show that the LSGCR_DTP algorithm can find the best solutions on about 81.5% conventional benchmarks, which outperforms state-of-the-art DTP solvers, including O_ABCDT, EA/G, ABC_DTP and GAITLS. Specially, the solution records of 7 instances are broken by LSGCR_DTP, and LSGCR_DTP can be used to solve many massive graphs with tens or even hundreds of thousand vertices which cannot be solved by the contrastive algorithm.
引用
收藏
页数:12
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