Chiranjib Patra¹, Pratyush², ¹Calcutta Institute of Engineering and Management, India and ²Jadavpur University, India

This paper introduces Vector Ant Colony Optimization (VACO), a distributed algorithm that is applied to solve the traveling salesman problem (TSP). In Any Colony System (ACS), a set of cooperating agents called ants cooperate to find good solutions of TSPs. Ants cooperate using an indirect form of communication mediated by pheromone they deposit on the edges of the TSP graph while building solutions. The proposed system (VACO) based on basic ACO algorithm with well distribution strategy in which the entire search area is initially divided into 2ⁿ number of hyper-cubic quadrants where n is the dimension of search space for updating the heuristic parameter in ACO to improve the performance in solving TSP. From our experiments, the proposed algorithm has better performance than standard bench mark algorithms.

Ant colony optimization, traveling salesman problem, pheromone, global minima, VACO.