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Recent advances in the analysis of distributed realtime systems have made it possible to predict if hard realtime requirements will be met. However, it is still difficult to find a feasible priority assignment when the utilization levels of the CPUs and communication networks are pushed near to their limits. This paper presents a new heuristic algorithm for optimizing the assignment of priorities to tasks and messages in distributed hard realtime systems. The algorithm is based on the knowledge of the parameters that influence the worst-case response time of a distributed application. This algorithm is compared to simulated annealing, which is a general optimization technique for discrete functions that had been previously used for solving similar problems. On average, our heuristic algorithm executes two orders of magnitude faster than simulated annealing, finds better solutions, and finds solutions in cases where the latter method fails.