Three factors determine the optimum configuration of a multiprocessor at any epoch: the workload, the reward structure, and the state of the computer system. An algorithm is presented for the optimal (more realistically, quasi-optimal) configuration of such systems used in real-time applications with periodic reward rates and workloads. The algorithm is based on Markov decision theory. It is suggested that a change in the workload or the reward structure should be as powerful a motivation for reconfiguration as component failure. Such changes occur naturally over the course of operation: an example of an online transaction processing system with a workload and reward structure that has a period of a day is given.