LAUSR

This article considers an admission quota control which determines the maximum daily admission (known as the quota) of controllable demand that shares capacity with uncontrollable demand. General arrival processes and general discrete stochastic service time are assumed. An infinite-horizon Markov decision process model is proposed to maximize the expected total discounted net reward comprising admission revenues and overcapacity costs. Through formal proofs, the optimal quota control which makes decisions before knowing demand information is found to be equivalent to the optimal classical admission control which makes decisions after knowing such information when the service time is deterministic or no more than two periods. This equivalence is shown numerically when the service time is no more than four periods. Furthermore, structural properties of the optimal quota control and bounds of the optimal quota are established. Finally, several heuristic policies are proposed and compared by numerical experiments.