Abstract
The uniform graph partitioning problem can be described as partitioning the nodes of a graph into two sets of equal size to minimize the sum of the cost of arcs having end-points in different sets. This problem has important applications in VLSI design, computer compiler design, and in placement and layout problems. The problem is known to be NP-complete. In this paper we propose two new heuristic procedures for solving the graph partitioning problem. The first is a straightforward extension of a local search algorithm, and the second is a genetic algorithm with features tailored for solving the graph partitioning problem. We compare these new procedures to Kernighan-Lin's algorithm, and to a procedure based on simulated annealing. Both extended local search and the genetic algorithm outperformed the simulated annealing procedure and Kernighan-Lin's algorithm with respect to the quality of the solutions. The genetic algorithm was found to be far more efficient than the other solution procedures.
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