This paper addresses the problem of static load balancing in heterogeneous distributed computing systems taking into account both memory and communication capacity constraints. It first models the load balancing problem as an optimization problem. It then presents a modified genetic algorithm, called Adaptive Genetic Algorithm (AGA), to solve the problem. The performance of the proposed algorithm is evaluated by simulation studies on randomly generated instances and the results are compared with that obtained by applying both the Genetic Algorithm (GA) and the Simulated Annealing (SA). Also, the qualities of the results are compared with the optimal solutions that obtained by applying the Brach-and-Bound (BB) algorithm.