Abstract
Partitioning is a fundamental problem in diverse fields of study such as data mining, parallel processing, and the design of VLSI circuits. A new approach to partition graphs and hypergraphs is introduced. This new approach combines local and global sampling, clustering, and Tabu search in a multilevel partitioning algorithm (TPART). TPART was implemented in a C program and compared to many state-of-the-art partitioning algorithms using a wide variety of benchmarks. TPART consistently performs well on the various benchmarks used and in comparison with other partitioning algorithms. TPART has a reasonably fast running time and it can produce a high quality partition of a graph of 262,144 nodes and 524,286 edges in less than 2 minutes CPU times on a Compaq Alpha DS20E 67/667 MHZ machine with 1GB of main memory.
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