  It is well-recognized that Air Cargo revenue management is quite different
from its passenger airline counterpart. Inherent demand volatility due to short
booking horizon and lumpy shipments, multi-dimensionality and uncertainty of
capacity as well as the flexibility in routing are a few of the challenges to
be handled for Air Cargo revenue management. In this paper, we present a
data-driven revenue management approach which is well-designed to handle the
challenges associated with Air Cargo industry. We present findings from
simulations tailored to Air Cargo setting and compare different scenarios for
handling of weight and volume bid prices. Our results show that running our
algorithm independently to generate weight and volume bid prices and summing
the weight and volume bid prices into price optimization works the best by
outperforming other strategies with more than 3% revenue gap.
