Experimental study of minimum cut algorithms

Recently, several new algorithms have been developed for the minimum cut problem. These algorithms are very different from the earlier ones and from each other and substantially improve the worst-case time bounds for the problem. In this paper, we conduct experimental evaluation the relative performance of these algorithms. In the process, we develop heuristics and data structures that substantially improve the practical performance of the algorithms. We also develop problem families for testing minimum cut algorithms. Our work leads to a better understanding of the practical performance of minimum cut algorithms and produces very efficient codes for the problem.