Title :
Ant colony system application to macrocell overlap removal
Author :
Alupoaei, Stelian ; Katkoori, Srinivas
Author_Institution :
Dept. of Comput. Sci. Eng., Univ. of South Florida, Tampa, FL, USA
Abstract :
We present a novel macrocell overlap removal algorithm, based on the ant colony optimization metaheuristic. The procedure generates a feasible placement from a relative placement with overlaps produced by some placement algorithms such as quadratic programming and force-directed. It uses the concept of ant colonies, a set of agents that work together to improve an existing solution. Each ant in the colony will generate a placement based on the relative positions of the cells and feedback information about the best placements generated by previous colonies. The solution of each ant is improved by using a local optimization procedure which reduces the unused space. The worst runtime is O(n/sup 3/), but the average runtime can be reduced to O(n/sup 2/).
Keywords :
circuit layout; circuit optimisation; graph theory; quadratic programming; ant colony optimization; ant colony system application; feasible placement; feedback information; macrocell overlap removal algorithm; placement algorithms; quadratic programming; Ant colony optimization; Costs; Feedback; Field programmable gate arrays; Iterative algorithms; Macrocell networks; Quadratic programming; Runtime; Shape; Traveling salesman problems;
Journal_Title :
Very Large Scale Integration (VLSI) Systems, IEEE Transactions on
DOI :
10.1109/TVLSI.2004.832926