A Local Search Algorithm with Vertex Weighting Strategy and Two-Level Configuration Checking for the Minimum Connected Dominating Set Problem

被引:0
|
作者
Li, Ruizhi [1 ,2 ,3 ]
He, Jintao [1 ]
Liu, Shangqiong [1 ]
Hu, Shuli [4 ]
Yin, Minghao [4 ]
机构
[1] Jilin Univ Finance & Econ, Sch Management Sci & Informat Engn, Changchun 130117, Peoples R China
[2] Business Big Data Res Ctr Jilin Prov, Changchun 130117, Peoples R China
[3] Jilin Univ, Key Lab Symbol Computat & Knowledge Engn, Minist Educ, Changchun 130012, Peoples R China
[4] Northeast Normal Univ, Sch Comp Sci & Informat Technol, Changchun 130117, Peoples R China
基金
中国国家自然科学基金;
关键词
perturbation strategy; simplification rule; scoring functions; minimum connected dominating set; TABU SEARCH; APPROXIMATION; ALLOCATION;
D O I
10.3390/biomimetics9070429
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The minimum connected dominating set problem is a combinatorial optimization problem with a wide range of applications in many fields. We propose an efficient local search algorithm to solve this problem. In this work, first, we adopt a new initial solution construction method based on three simplification rules. This method can reduce the size of the original graph and thus obtain a high-quality initial solution. Second, we propose an approach based on a two-level configuration checking strategy and a tabu strategy to reduce the cycling problem. Third, we introduce a perturbation strategy and a vertex weighting strategy to help the algorithm be able to jump out of the local optimum effectively. Fourth, we combine the scoring functions Cscore and Mscore with the aforementioned strategies to propose effective methods for selecting vertices. These methods assist the algorithm in selecting vertices that are suitable for addition to or removal from the current candidate solution. Finally, we verify the performance advantages of the local search algorithm by comparing it with existing optimal heuristic algorithms on two sets of instances. The experimental results show that the algorithm exhibits better performance on two sets of classical instances.
引用
收藏
页数:19
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