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A new meta-heuristic method of ant colony algorithm called SbMACA is developed for solving the Capacitated Vehicle Routing Problem (CVRP). The SbMACA is different from other ACAs developed before in four aspects. First, at the beginning of constructing each new subtour during the route construction, ant does not depart from the depot, but randomly from the vertices that have not been visited so far. Secondly, ants in nature could not sense the pheromone until its amount is greater than certain threshold. Therefore, similarly in the SbMACA, when the ants select the next vertex to transit, the pheromone would be neglected if its amount is less than the prespecified threshold. Thirdly, once the ants have constructed their solutions, each ant's solution might be improved by applying Sweep Algorithm which makes improvement to the solutions by exchanging the vertices between subtours. Finally, a new Multiple Ant Colonies technique is proposed, in which multiple ant colonies are executed separately and simultaneously, and after all colonies are in the state of stagnation, communication among them is carried out in order to do favor to leave the local peaks. Experiment shows that the SbMACA is able to find solutions for CVRP within 0.28% of known optimal solutions and is one of the best ACA heuristics developed so far. Additionally, the performance of SbMACA is compared with that of other ACA heuristics and another meta-heuristics Tabu Search respectively.