Abstract—The Classical floor planning that usually handles only block packing to minimize silicon area, So modern floorplanning could be formulated as a fixed-outline floor planning. It uses some algorithms such as B-TREE representation, simulated annealing and adaptive fast simulated annealing. Comparing above three algorithms the better efficient solution came from adaptive fast simulated annealing, its leads to faster and more stable convergence to the desired floorplan solutions. But the results are not an optimal solution. To get an optimal solution its necessary to choose effective algorithm. Combining global and local search is a strategy used by many hybrid optimization approaches. Memetic Algorithm (MA) is an evolutionary Algorithm that includes one or more local search phases within its evolutionary cycle. MA applies some sort of local search to improve the fitness of individuals in the population. The algorithm combines a hierarchical design technique, Genetic algorithms, constructive techniques and advanced local search to solve VLSI floor planning problem. MA quickly produces optimal or nearly optimal solutions for all the popular benchmark problems.
Index Terms—Floorplan Problem, Memetic algorithm, Genetic Algorithm, Delay, Cut size.
Hameem Shanavas I. is the research Scholar of Anna University, Coimbatore, India.
Dr. R. K. Gnanamurthy is a Prof of Information and Communication Engineering, Anna University, Coimbatore, India
Cite: Hameem Shanavas I. and Gnanamurthy R. K., "Evolutionary Algorithmical Approach for VLSI Floorplanning Problem," International Journal of Computer Theory and Engineering vol. 1, no. 4, pp. 461-464, 2009.