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10.5120/ijca2016910453 |
Reshu Tyagi and Muskaan Batra. Implementation and Comparison of Vertex Cover Problem using Various Techniques. International Journal of Computer Applications 144(10):26-31, June 2016. BibTeX
@article{10.5120/ijca2016910453, author = {Reshu Tyagi and Muskaan Batra}, title = {Implementation and Comparison of Vertex Cover Problem using Various Techniques}, journal = {International Journal of Computer Applications}, issue_date = {June 2016}, volume = {144}, number = {10}, month = {Jun}, year = {2016}, issn = {0975-8887}, pages = {26-31}, numpages = {6}, url = {http://www.ijcaonline.org/archives/volume144/number10/25216-2016910453}, doi = {10.5120/ijca2016910453}, publisher = {Foundation of Computer Science (FCS), NY, USA}, address = {New York, USA} }
Abstract
The problem of finding Minimum Vertex Cover for graph belongs to the class of NP Complete and plays a key role in Computer Science Theory. The problems which belong to NP Complete set are not solvable in polynomial time in any known way. Since finding Minimum Vertex Cover (MVC) for a graph belongs to NP Complete class; so we are dubious to solve it in any polynomial time algorithm. Such problems are solved by algorithms which promise to give near optimum solution.
In this paper we have analyzed and scrutinized such algorithms like greedy algorithm, approximation algorithm, simple genetic algorithm (GA), primal-dual based algorithm (PDB), Alom’s algorithm etc. on random directed and undirected graphs and found that all the algorithms give near optimum solution with a negligible performance difference. It was also observed that out of all the above said algorithms Alom’s Algorithm is more effective in finding MVC for undirected graphs and for weighted graphs, superior performance is attained by primal-dual based approach.
Further the algorithm was implemented using JAVA and output demonstrates the various possible combinations of Minimum Vertex Cover.
References
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Keywords
Vertex Cover, Approximation, Branch and Bound, Greedy, Alom’s, Primal Dual, Genetic.