Graph Theory and Algorithms for Network Analysis

Efficient Graph Algorithms for Network Analysis

We provide efficient algorithms for two major problems in network analysis. One is the Graph Center (GC) problem and the other is the Graph Bottleneck (GB) problem. The GC problem is relevant for facility location, while the GB problem is relevant for transportation and logistics. The GC problem is to identify a pre-determined number of center vertices such that the distances or costs from (or ...

Clustering Algorithms for Anti-Money Laundering Using Graph Theory and Social Network Analysis

HEMOLIA (a project under European community’s 7th framework programme) is a new generation Anti-Money Laundering (AML) intelligent multi-agent alert and investigation system which in addition to the traditional financial data makes extensive use of modern society’s huge telecom data source, thereby opening up a new dimension of capabilities to all Money Laundering fighters (FIUs, LEAs) and Fina...

Analysis of the enzyme network involved in cattle milk production using graph theory

Understanding cattle metabolism and its relationship with milk products is important in bovine breeding. A systemic view could lead to consequences that will result in a better understanding of existing concepts. Topological indices and quantitative characterizations mostly result from the application of graph theory on biological data. In the present work, the enzyme network involved in cattle...

Algorithms in Graph Theory

Graph Algorithms for Network Connectivity Problems

This paper surveys the recent progress on the graph algorithms for solving network connectivity problems such as the extreme set problem, the cactus representation problem, the edge-connectivity augmentation problem and the source location problem. In particular, we show that efficient algorithms for these problems can be designed based on maximum adjacency orderings.