Ant Colony System (ACS) is a well known optimization algorithm to find a good route solution for logistics and transportation industries such as Traveling Salesman Problem (TSP) or Vehicle Routing Problem (VRP), for the company maximize the efficiency and resource. Several versions of Ant Colony Optimization (ACO) algorithms have been proposed which aim to achieve an optimum solution includes Dynamic Ant Colony System with Three Level Updates (DACS3). DACS3 is an enhancement of ACS which focuses on adding individual ant behavior. The algorithm works better in TSP solution. This research aims to see the performance of DACS3 in VRP domain. The result shows that DACS3 has achieved a better solution for most the datasets of Capacitated Vehicle Routing Problem (CVRP). Embedding a simple behavior of a single ant influences its achievement to reach an optimal distance and also can perform considerably faster compare to other algorithm in TSP and CVRP.