The performance of a parallel application running on a Distributed Computing System (DCS) is basically affected by the distribution of workload over the various processors in the system. This problem is known to be NP-hard in most cases and complicates farther with increasing number of tasks and/or computers. This paper presents two heuristic algorithms; Simulated Annealing (SA) and Genetic Algorithm (GA), to solve the mentioned problem. The qualities of the resulting distribution are compared with that obtained by applying the Branch–and-Bound (BB) technique.