An Enhanced Algorithm for Floorplan Design Using Hybrid Ant Colony and Particle Swarm Optimization

Abstract

Floorplanning is the very first stage of the Very Large Scale Integrated-circuit (VLSI) physical design process, the resultant quality of which is very important for successive design stages. Floorplanning deals with position, shape and movement of the circuit modules and make sure that no of them overlaps. It aims at minimizing the total layout area and interconnection wire length. Several algorithms have been deployed for floorplanning optimization problems. Here we use a hybrid Ant Colony and Particle Swarm optimization algorithm. Although PSO has simple principle and easy to be implemented and can eventually locate the desired solution, however, its practical use in solving engineering optimization problems is severely limited by the high computational cost and slow convergence rate. Hence, Ant Colony optimization is employed to speed up local search and to improve the precision of the solution. Adding some abilities of ACO to the PSO algorithm improves the performance of the resultant hybrid algorithm.

Authors and Affiliations

Prabhjit Kaur

Keywords

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  • EP ID EP18785
  • DOI -
  • Views 390
  • Downloads 9

How To Cite

Prabhjit Kaur (2014). An Enhanced Algorithm for Floorplan Design Using Hybrid Ant Colony and Particle Swarm Optimization. International Journal for Research in Applied Science and Engineering Technology (IJRASET), 2(9), -. https://europub.co.uk/articles/-A-18785