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- W1819860449 abstract "In this paper, we study optimal revenue management applied to carparks, with primary objective to maximizerevenues under a continuous-time framework. We develop a stochastic discrete-time model and propose arejection algorithm that makes optimal decisions (accept/reject) according to the future expected revenuesgenerated and on the opportunity cost that arises before each sale. For this aspect of the problem, a MonteCarlo approach is used to derive optimal rejection policies. We then extend this approach to show that thereexists an equivalent continuous-time methodology that yields to a partial differential equation (PDE). Thenature of the PDE, as opposed to theMonte Carlo approach, generates the rejection policies quicker and causesthe optimal surfaces to be significantly smoother. However, because the solution to the PDE is considered notto solve the `full' problem, we propose an approach to generate optimal revenues using the discrete-timemodel by exploiting the information coming from the PDE. We give a worked example of how to generatenear-optimal revenues with an order of magnitude decrease in computation speed." @default.
- W1819860449 created "2016-06-24" @default.
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- W1819860449 date "2012-01-01" @default.
- W1819860449 modified "2023-09-23" @default.
- W1819860449 title "CONTINUOUS-TIME REVENUE MANAGEMENT IN CARPARKS" @default.
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- W1819860449 doi "https://doi.org/10.5220/0003762800730082" @default.
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