出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：This paper introduces Vector Ant Colony Optimization (VACO), a distributed algorithm that isapplied to solve the traveling salesman problem (TSP). In Any Colony System (ACS), a set ofcooperating agents called ants cooperate to find good solutions of TSPs. Ants cooperate usingan indirect form of communication mediated by pheromone they deposit on the edges of the TSPgraph while building solutions. The proposed system (VACO) based on basic ACO algorithmwith well distribution strategy in which the entire search area is initially divided into 2nnumberof hyper-cubic quadrants where n is the dimension of search space for updating the heuristicparameter in ACO to improve the performance in solving TSP. From our experiments, theproposed algorithm has better performance than standard bench mark algorithms.
关键词：Ant colony optimization; traveling salesman problem; pheromone; global minima; VACO.
