A novel robust memetic algorithm for dynamic community structures detection in complex networks

Networks in the real world are dynamic and evolving. The most critical process in networks is to determine the structure of the community, based on which we can detect hidden communities in a complex network. The design of strong network structures is of great importance, meaning that a system must...

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Bibliographic Details
Published in:World wide web (Bussum) 2024, Vol.27 (1), p.3, Article 3
Main Authors: Ranjkesh, Somayeh, Masoumi, Behrooz, Hashemi, Seyyed Mohsen
Format: Article
Language:English
Subjects:
Algorithms
Computer Science
Database Management
Information Systems Applications (incl.Internet)
Network topologies
Operating Systems
Optimization
Robustness
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Summary:Networks in the real world are dynamic and evolving. The most critical process in networks is to determine the structure of the community, based on which we can detect hidden communities in a complex network. The design of strong network structures is of great importance, meaning that a system must maintain its function in the face of attacks and failures and have a strong community structure. In this paper, we proposed the robust memetic algorithm and used the idea to optimize the detection of dynamic communities in complex networks called RDMA_NET (Robust Dynamic Memetic Algorithm). In this method, we work on dynamic data that affects the two main parts of the initial population value and the calculation of the evaluation function of each population, and there is no need to determine the number of communities in advance. We used two sets of real-world networks and the LFR dataset. The results show that our proposed method, RDMA_Net, can find a better solution than modern approaches and provide near-optimal performance in search of network topologies with a strong community structure.
ISSN:1386-145X
1573-1413
DOI:10.1007/s11280-024-01238-7