GENETIC ALGORITHM FOR NODE PARTITIONING PROBLEM AND APPLICATIONS IN VLSI DESIGN

The group of classical graph-theoretic problems, including graph colou ring, clique cover, and maximal clique, may be viewed as instances of a general node partitioning problem (NPP). A wide variety of real life problems can be modelled as instances of NPP. Finding an optimal part ition for the NPP is said to be NP-complete. In this work a stochastic search by a genetic algorithm (GA) is employed to find a near optimal solution for the NPP. The critical aspects of the GA for NPP, such as the solution representation by elegant data structure, together with genetic operations and selection policies employed in the GA procedure , are also presented. The proposed GA does not require the number of d isjunct node sets to be given a priori. Three application problems is VLSI design are solved as instances of NPP. The experimental results p resented in each case of these application problems bring out the effi cacy of genetic algorithms.