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Matthias Koenig, Joern Meissner
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| Abstract |
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Consider a single-leg dynamic revenue management problem with fare classes controlled
by capacity in a risk-averse setting. The revenue management strategy aims
at limiting the down-side risk, and in particular, value-at-risk. A value-at-risk optimised
policy offers an advantage when considering applications which do not
allow for a large number of reiterations. They allow for specifying a confidence
level regarding undesired scenarios.
We state the underlying problem as a Markov decision process and provide a
computational method for computing policies, which optimise the value-at-risk for
a given confidence level. This is achieved by computing dynamic programming solutions
for a set of target revenue values and combining the solutions in order to
attain the requested multi-stage risk-averse policy. Numerical examples and comparison
with other risk-sensitive approaches are discussed. |
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| Keywords |
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Capacity Control, Revenue Management, Risk, Value-at-Risk
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| Status |
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Working Paper |
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| Download |
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www.meiss.com/download/RM-Koenig-Meissner-04.pdf
(167 kb) |
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| Reference |
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BibTeX,
Plain Text |
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