An improved circuit-partitioning algorithm based on min-cut equivalence relation
Integration, the VLSI Journal
Embedding Intelligence into EDA Tools
Proceedings of the 2006 conference on Integrated Intelligent Systems for Engineering Design
Lower and upper bounds for linkage discovery
IEEE Transactions on Evolutionary Computation
A survey on chromosomal structures and operators for exploiting topological linkages of genes
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartII
New usage of SOM for genetic algorithms
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
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A genetic algorithm for partitioning a hypergraph into two disjoint graphs of minimum ratio cut is presented. As the Fiduccia-Mattheyses graph partitioning heuristic turns out to be not effective when used in the context of a hybrid genetic algorithm, we propose a modification of the Fiduccia-Mattheyses heuristic for more effective and faster space search by introducing a number of novel features. We also provide a preprocessing heuristic for genetic encoding designed solely for hypergraphs which helps genetic algorithms exploit clustering information of input graphs. Supporting combinatorial arguments for the new preprocessing heuristic are also provided. Experimental results on industrial benchmarks circuits showed visible improvement over recently published algorithms with a lower growth rate of running time