Fast Internet connections and the widespread use of high performance graphic cards are making distributed virtual environment systems very common nowadays. However, there are several key issues in these systems that should still be improved in order to design a scalable and cost-effective DVE system. One of these key issues is the partitioning problem. This problem consists of efficiently assigning clients (3D avatars) to the servers in the system. This paper proposes a new implementation of the ant colony system (ACS) search method for solving the partitioning problem in DVE systems. The ACS method is an heuristic search method based on evolutionary computation. Performance evaluation results show that, due to its ability for both finding good search paths and escaping from local minima, the proposed method can provide better solutions with shorter execution times than the methods proposed in the literature, particularly for large DVE systems. Therefore, the proposed implementation of the ACS search method improves the scalability and efficiency of DVE systems.