A supervisor of a discrete-event system can prohibit controllable events to ensure the safety and liveness specifications of the system. However， the supervisor does not actively select the controllable events that are allowed to occur， so it is possible that several controllable events occur simultaneously. In practice， such as traffic scheduling and robot path planning， the system is required to allow at most one controllable event to occur in each state. In response to the above problem， an optimal mechanism was introduced to quantify control cost， and an optimal supervisory control algorithm of discrete-event systems was proposed， which not only can guarantee the safety and liveness of the system， but also can minimize the cumulative cost of event execution. Firstly， the automata model of controlled system and behavioral constraints was given， and a nonblocking supervisor with maximum allowable behaviors was solved on the basis of the supervisory control theory of Ramadge and Wonham. Secondly， a cost function was defined to assign the corresponding cost to the execution of each event in the supervisor. Finally， an optimal directed supervisor was calculated iteratively based on dynamic programming to achieve the goals of at most one controllable event occurring in each state and minimizing the cumulative cost of event execution. To verify the effectiveness and correctness of the proposed algorithm， a one-way train guideway example and a multi-track train control example were used. For the above two examples， the cumulative cost of the event execution required for the directed supervisor solved by the proposed algorithm to reach the target state is 26.0 and 14.0 respectively， which is lower than the 27.5 and 16.0 of greedy algorithm and the 26.5 and 14.0 of Q-learning.