A memory-based simulated annealing algorithm and a new auxiliary function for the fixed-outline floorplanning with soft blocks.

A memory-based simulated annealing (MSA) algorithm is proposed for the fixed-outline floorplanning with soft blocks. MSA constructs a memory pool to store some historical best solutions. Moreover, it adopts a real-time monitoring strategy to check whether a solution has been trapped in a local optimum. In case a solution encounters this predicament, it will be replaced by the one from the memory pool, and the current temperature will be regenerated by continuously perturbing the new solution several times. To meet the fixed-outline requirements, a new auxiliary function is formulated based on the geometric structure of the current floorplan, and it is very helpful in driving MSA to search towards potential solution space. Concretely, the area information of all violated blocks is utilized to construct an auxiliary function. Moreover, the excessive area of a violated block can be weighted by three different coefficients, which depend on the relative position of the block and the fixed-outline. Additionally, due to its simple topology and strong applicability, B ⋆ -tree representation is employed to perturb a solution in each generation. The efficiency of the proposed method is demonstrated on six GSRC floorplan benchmark examples with various white space and aspect ratios. Two groups of Matlab simulations show that our approach can achieve better floorplanning results and satisfy both the fixed-outline and non-overlapping constraints while optimizing circuit performance. [ABSTRACT FROM AUTHOR]