A new approach to the maximum-flow problem
Journal of the ACM (JACM)
The Stanford GraphBase: a platform for combinatorial computing
The Stanford GraphBase: a platform for combinatorial computing
A faster algorithm for finding the minimum cut in a directed graph
SODA selected papers from the third annual ACM-SIAM symposium on Discrete algorithms
Parallel Methods for VLSI Layout Design
Parallel Methods for VLSI Layout Design
ECAL '99 Proceedings of the 5th European Conference on Advances in Artificial Life
A divide-and-merge methodology for clustering
ACM Transactions on Database Systems (TODS)
First steps to the runtime complexity analysis of ant colony optimization
Computers and Operations Research
An effective multi-level algorithm based on ant colony optimization for bisecting graph
PAKDD'07 Proceedings of the 11th Pacific-Asia conference on Advances in knowledge discovery and data mining
Ant system: optimization by a colony of cooperating agents
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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We investigate the usage of Ant Colony Optimization to detect balanced graph cuts. In order to do so we develop an algorithm based on competing ant colonies. We use a heuristic from social network analysis called the edge clustering coefficient, which greatly helps our colonies in local search. The algorithm is able to detect cuts that correspond very well to known cuts on small real-world networks. Also, with the correct parameter balance, our algorithm often outperforms the traditional Kernighan-Lin algorithm for graph partitioning with equal running time complexity. On larger networks, our algorithm is able to obtain low cut sizes, but at the cost of a balanced partition.