  This paper tackles the problem of finding optimal variable-height transport
packaging. The goal is to reduce the empty space left in a box when shipping
goods to customers, thereby saving on filler and reducing waste. We cast this
problem as a large-scale mixed integer problem (with over seven billion
variables) and demonstrate various acceleration techniques to solve it
efficiently in about three hours on a laptop. We present a KD-Tree algorithm to
avoid exhaustive grid evaluation of the 3D-bin-packing, provide analytical
transformations to accelerate the Benders decomposition, and an efficient
implementation of the Benders sub problem for significant memory savings and a
three order of magnitude runtime speedup.
