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Ant colony system application to macrocell overlap removal

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2 Author(s)
Alupoaei, S. ; Dept. of Comput. Sci. Eng., Univ. of South Florida, Tampa, FL, USA ; Katkoori, S.

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/).

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Very Large Scale Integration (VLSI) Systems, IEEE Transactions on  (Volume:12 ,  Issue: 10 )