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

Dynamic Allocation Problems in Loss Network Systems with Advanced Reservation