A novel local search approach with connected dominating degree-based incremental neighborhood evaluation for the minimum 2-connected dominating set problem
{"title":"A novel local search approach with connected dominating degree-based incremental neighborhood evaluation for the minimum 2-connected dominating set problem","authors":"Mao Luo, Huigang Qin, Xinyun Wu, Caiquan Xiong","doi":"10.1007/s10878-024-01175-1","DOIUrl":null,"url":null,"abstract":"<p>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.</p>","PeriodicalId":50231,"journal":{"name":"Journal of Combinatorial Optimization","volume":"16 1","pages":""},"PeriodicalIF":0.9000,"publicationDate":"2024-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Combinatorial Optimization","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1007/s10878-024-01175-1","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
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.
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.