2005/09/30 by Bing Wang, Huanwen Tang, Chonghui Guo +2 · 43 citations
Biochemistry, Genetics and Molecular Biology · Mathematics · Physics and Astronomy · #Algorithm #Artificial intelligence #Cluster analysis #Complex Network Analysis Techniques #Computer science #Gene Regulatory Network Analysis #Mathematical optimization #Mathematics #Network formation #Opinion Dynamics and Social Influence #Random graph #Resilience (materials science) #Simple (philosophy) #Tabu search #Theoretical computer science #cond-mat.dis-nn
paper · pdf · doi:10.1016/j.physa.2005.12.050
published in Physica A Statistical Mechanics and its Applications 368(2), 607-614 (Elsevier BV) · 11 pages, 6 figures, accepted by Physica A
arxiv created 2005/12/24 · openalex publication_date 2006/01/24 · arxiv updated 2009/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
Network's resilience to the malfunction of its components has been of great concern. The goal of this work is to determine the network design guidelines, which maximizes the network efficiency while keeping the cost of the network (that is the average connectivity) constant. With a global optimization method, memory tabu search (MTS), we get the optimal network structure with the approximately best efficiency. We analyze the statistical characters of the network and find that a network with a small quantity of hub nodes, high degree of clustering may be much more resilient to perturbations than a random network and the optimal network is one kind of highly heterogeneous networks. The results strongly suggest that networks with higher efficiency are more robust to random failures. In addition, we propose a simple model to describe the statistical properties of the optimal network and investigate the synchronizability of this model.