Ant colony optimization technique for macrocell overlap removal

Author

Alupoaei, Stelian ; Katkoori, Srinivas

Author_Institution

Dept. of Comput. Sci. & Eng., Univ. of South Florida, Tampa, FL, USA

fYear

2004

fDate

2004

Firstpage

963

Lastpage

968

Abstract

We present a novel macrocell overlap removal algorithm, based on the ant colony optimization (ACO) metaheuristic. The algorithm 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.

Keywords

cellular arrays; feedback; graphs; integrated circuit layout; quadratic programming; ant colony optimization; feedback information; floorplanning; graphs; macrocell overlap removal algorithm; placement algorithms; quadratic programming; Ant colony optimization; Computer science; Costs; Feedback; Field programmable gate arrays; Iterative algorithms; Macrocell networks; Quadratic programming; Traveling salesman problems; Very large scale integration;

fLanguage

English

Publisher

ieee

Conference_Titel

VLSI Design, 2004. Proceedings. 17th International Conference on

Print_ISBN

0-7695-2072-3

Type

conf

DOI

10.1109/ICVD.2004.1261055

Filename

1261055