Ant colony optimization technique for macrocell overlap removal

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.