An efficient genetic algorithm for slicing floorplan area optimization

In this paper, we develop a new genetic algorithm that can efficiently solve the floorplan area optimization problem. The algorithm merges the properties of encoding schemes of slicing trees and the evolutional mechanism of genetic algorithms. A novel genetic operator, which always inherits good properties from ancestors in the algorithm, is proposed to effectively explore solution space. Experimental results show that the developed algorithm achieves comparable computation time and performance quality to the nonslicing state-of-the-art ones.