An Improvement to Ant Colony Optimization Heuristic
ISNN '08 Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks
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It is known that ant colony optimization (ACO) algorithm has been successfully applied to solve many combinatorial optimization problems, but for p-median problem little has been reported. In this article, a new heuristic is proposed for capacitated p-median problem. This algorithm adopts pheromone mechanism to learn the probability in which an object belongs to a median. Also a suitable classification method is designed based on the problem's characteristics. At last, 10 benchmark problems are used to demonstrate the global optimization ability of the algorithm. The obtained results show that our algorithm is feasible and efficient.