Abstract | ||
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The Critical Node Problem (CNP) aims to identify k nodes from an undirected graph G=(V,E), in order to minimize the number of pairwise connected nodes in the residual graph after deleting these k nodes. This problem has a wide range of applications in the fields of cyber security, disease control, biological analysis, social network, etc. The CNP is known to be NP-hard, and heuristics are commonly used to solve large-scale CNP instances, among which the node-exchange operation is a basic move operator widely adopted by local-search based heuristics. Given an initial CNP solution consisting of k nodes, there are totally k×(|V|−k) possible node-exchange operations. The current best algorithm requires a complexity of O((|V|−k)×(|V|+|E|+k×D(G))) to evaluate all these operations (|V| denotes the number of nodes, |E| denotes the number of edges, D(G) denotes the maximum degree of the node in graph G).In this paper, a series of dynamic data structures are implemented to reduce the above complexity to O((|V|−k)×(|V|+|E|)), so as to improve the efficiency of local search. |
Year | DOI | Venue |
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2018 | 10.1109/CCIS.2018.8691236 | 2018 5th IEEE International Conference on Cloud Computing and Intelligence Systems (CCIS) |
Keywords | Field | DocType |
Critical Node Problem,Node-Exchange Operator,Dynamic Data Structure | Pairwise comparison,Discrete mathematics,Graph,Computer science,Disease control,Heuristics,Degree (graph theory),Operator (computer programming),Local search (optimization),Dynamic data structures,Distributed computing | Conference |
ISSN | ISBN | Citations |
2376-5933 | 978-1-5386-6005-8 | 0 |
PageRank | References | Authors |
0.34 | 0 | 5 |
Name | Order | Citations | PageRank |
---|---|---|---|
Xiangrong Zeng | 1 | 10 | 5.20 |
Siyang Liu | 2 | 0 | 2.03 |
LiFan Shen | 3 | 0 | 0.34 |
Yong-Quan Chen | 4 | 4 | 3.12 |
Zhang-Hua Fu | 5 | 27 | 6.49 |