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We present an efficient algorithm for exact calculation and minimization of expected waiting times of all passengers using a bank of elevators. The dynamics of the system are represented by a discrete-state Markov chain embedded in the continuous phase-space diagram of a moving elevator car. The chain is evaluated efficiently using dynamic programming to compute measures of future system performance such as expected waiting time, properly averaged over all possible future scenarios. A linear-time elevator group controller based on this method significantly outperforms benchmark algorithms and is completely within the computational capabilities of contemporary elevator bank controllers.