Vertex Cover Optimization Using a Novel Graph Decomposition Approach

The minimum vertex cover problem (MVCP) is a well-known combinatorial optimization of graph theory. MVCP an NP (nondeterministic polynomial) complete and it has exponential growing complexity with respect to the size graph. No algorithm exits till date that can exactly solve in deterministic polynomial time scale. However, several algorithms are proposed approximately short Such useful for large graphs, which exact solution impossible current computational resources. wide range applications fields like bioinformatics, biochemistry, circuit design, electrical engineering, data aggregation, networking, internet traffic monitoring, pattern recognition, marketing franchising etc. This work aims by novel decomposition approach. yields subgraph contains edges shared triangular edge structures. A covered yield forms one or more Hamiltonian cycles paths. In order reduce new strategy also proposed. reduction be used any solving MVCP. Based on strategy, two formulated These tested using well known standard benchmark graphs. key feature results good approximate error ratio improvement optimum values few