We consider congestion control in a non-stationary queueing system. Assuming that the arrival and service rates are measurable, bounded, and periodic functions of time, a Markovdecision process (MDP) formulation is developed. We show under infinite horizon discounted and average reward optimality criterion, for each fixed time, optimal pricing and admission
control strategies are non-decreasing in the number of customers in the system. This extends
well-known stationary results to the non-stationary setting. However, even with this insight,
solution of the problem is intractable. We propose an easily implementablepointwise stationary
approximation(PSA) to approximate the optimal policies in each case, and suggest a heuristic
to improve the implementation of the PSA and verify its usefulness via a numerical study.