We propose a memetic algorithm based approach for allocating objects in distributed computing environment. Our allocation objective is to allocate objects to different servers so that the number of inter-server communications can be minimized. Assuming servers with similar processing and storage capabilities - to avoid biased allocation of the objects on servers with higher performance - we formulate the problem of allocating distributed objects as a graph bisection problem. Using simulated data, we use the memetic algorithm to solve the graph bisection problem. We compare the performance of the memetic algorithm with the Kernighan and Lin (KL) heuristic and semidefinite programming (SDP) lower bounds for graph bisection problem. The results of our experiments show that the memetic algorithm performs better or equal to the KL heuristic and has a relative performance gap of between 2-5% from the SDP lower bounds.