Hybrid Genetic Algorithm for VLSI Macro Cell Layout
Genetic algorithms have proven to be a well-suited technique for solving selected combinatorial optimization problems. The blindness of the algorithm during the search in the space of encoding must be abandoned, because this space is discrete and the search has to reach feasible points after the application of the genetic operators. This can be achieved by the use of a problem specific genotype encoding, and hybrid, knowledge based techniques, which support the algorithm during the creation of the initial individuals and the following optimization process. In this paper a novel hybrid genetic algorithm, which is used to solve macro-cell placement problem is presented. Two new heuristics are introduced. Due to a tree-structured genotype representation and hybrid, problem- specific operators, the proposed approach is able to show satisfactory performance.
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