Enhancing scheduling solutions through ant colony optimization

In this paper a methodology based on ant colony optimization is presented to generate optimal scheduling during high-level synthesis. The classical force equation of the force-directed scheduling algorithm has been modified to accommodate the experiences accumulated by multiple agents in different iterations. In each iteration the obtained schedule is subjected to remaining steps of synthesis using standard techniques like clique partitioning for resource allocation and left edge algorithm. The results are used to improve scheduling in the next iteration.