• DocumentCode
    1111704
  • 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
  • Volume
    12
  • Issue
    10
  • fYear
    2004
  • Firstpage
    1118
  • Lastpage
    1123
  • 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;
  • fLanguage
    English
  • Journal_Title
    Very Large Scale Integration (VLSI) Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1063-8210
  • Type

    jour

  • DOI
    10.1109/TVLSI.2004.832926
  • Filename
    1336857