A novel local search approach with connected dominating degree-based incremental neighborhood evaluation for the minimum 2-connected dominating set problem

IF 0.9 4区 数学 Q4 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Journal of Combinatorial Optimization Pub Date : 2024-05-14 DOI:10.1007/s10878-024-01175-1
Mao Luo, Huigang Qin, Xinyun Wu, Caiquan Xiong
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Abstract

The minimum connected dominating set problem is widely studied due to its applicability to mobile ad-hoc networks and sensor grids. Its variant the minimum 2-connected dominating set (M-2CDS) problem has become increasingly important because its critical role in designing fault-tolerant network. This paper presents a connected dominating degree-based local search (CDD-LS) tailored for solving the M-2CDS. The proposed algorithm implements an improved swap-based neighborhood structure as well as the corresponding fast neighborhood evaluation method using connected dominating degree data structure. The diversification techniques including tabu strategy and perturbaistion help the search jump out of the local optima improving the efficiency. This study investigates the performance of the CDD-LS algorithm on 38 publicly available benchmark datasets. The results demonstrate that the CDD-LS algorithm significantly improves the best runtime in 19 instances, while providing the equivalent performance in 8 instances. Furthermore, the CDD-LS is tested on 18 newly generated instances to check its capability on large-scale scenarios. To gain a deeper understanding of the algorithm’s effectiveness, an investigation into the key components of the CDD-LS algorithm is conducted.

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针对最小 2 连接支配集问题的基于连接支配度增量邻域评估的新型局部搜索方法
最小连接支配集问题因其适用于移动 ad-hoc 网络和传感器网格而被广泛研究。它的变种--最小二连接支配集(M-2CDS)问题在设计容错网络中起着至关重要的作用,因此变得越来越重要。本文提出了一种基于连接支配度的局部搜索(CDD-LS),专门用于解决 M-2CDS 问题。所提出的算法实现了一种改进的基于交换的邻域结构,并利用连通支配度数据结构实现了相应的快速邻域评估方法。包括塔布策略和 perturbaistion 在内的多样化技术有助于搜索跳出局部最优,从而提高效率。本研究调查了 CDD-LS 算法在 38 个公开基准数据集上的性能。结果表明,CDD-LS 算法在 19 个实例中显著提高了最佳运行时间,同时在 8 个实例中提供了同等性能。此外,CDD-LS 还在 18 个新生成的实例上进行了测试,以检验其在大规模场景中的能力。为了更深入地了解该算法的有效性,我们对 CDD-LS 算法的关键组件进行了研究。
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来源期刊
Journal of Combinatorial Optimization
Journal of Combinatorial Optimization 数学-计算机:跨学科应用
CiteScore
2.00
自引率
10.00%
发文量
83
审稿时长
6 months
期刊介绍: The objective of Journal of Combinatorial Optimization is to advance and promote the theory and applications of combinatorial optimization, which is an area of research at the intersection of applied mathematics, computer science, and operations research and which overlaps with many other areas such as computation complexity, computational biology, VLSI design, communication networks, and management science. It includes complexity analysis and algorithm design for combinatorial optimization problems, numerical experiments and problem discovery with applications in science and engineering. The Journal of Combinatorial Optimization publishes refereed papers dealing with all theoretical, computational and applied aspects of combinatorial optimization. It also publishes reviews of appropriate books and special issues of journals.
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