  We consider a class of well-known dynamic resource allocation models in loss
network systems with advanced reservation. The most important performance
measure in any loss network system is to compute its blocking probability,
i.e., the probability of an arriving customer in equilibrium finds a fully
utilized system (thereby getting rejected by the system). In this paper, we
derive upper bounds on the asymptotic blocking probabilities for such systems
in high-volume regimes. There have been relatively few results on loss network
systems with advanced reservation due to its inherent complexity. The
theoretical results find applications in a wide class of revenue management
problems in systems with reusable resources and advanced reservation, e.g.,
hotel room, car rental and workforce management. We propose a simple control
policy called the improved class selection policy (ICSP) based on solving a
continuous knapsack problem, similar in spirit to the one proposed in Levi and
Radovanovic (2010). Using our results derived for loss network systems with
advanced reservation, we show the ICSP performs asymptotically near-optimal in
high-volume regimes.
