Marginal Revenue-Based Capacity Management Models and Benchmark1

To efficiently meet customer requirements, a manager must supply adequate quantity of products, or capacity, or services at the right time with the right price. Revenue management technique can help firms to use differential pricing strategies and capacity allocation tactics to maximize revenue. In this paper, we propose Marginal Revenue-Based Capacity Management (MRBCM) models based on revenue management principle to manage stochastic demand at a micro-level to create revenue opportunities. In particular, MRBCM models are created to generate order acceptance policy, that is, to allocate available capacity for promising to alternative market segments. In our illustration, products are classified by revenue contribution in their respective capacity unit, low, middle, and high. In three models (MRBCMa, MRBCMb, MRBCMc), the amounts of capacity are reserved for the high and middle revenue classes. As an enhancement, MRBCMb and MRBCMc models consider opportunity revenue and cost in various completed fashions. To evaluate these models, we design and conduct simulations for 16 scenarios and compare three MRBCM models and two simple methods with the First-Come-First-Served (FCFS) policy in a single planning horizon. The experimental results show that MRBCM models generate significant higher profits over FCFS rule at each scenario