Cutting problems are problems where a certain large object should be cut to several small objects. For example, imagine you have a factory that works with large sheets of raw glass, of width $W$ and length $L$. There are several buyers, each of which wants an unbounded number of small glass sheets. Buyer $i$ wants sheets of length $l_i$ and width $w_i$. Your goal is to cut small sheets from the large one, such that the total used is maximized and the waste is minimized (there are also other types of cutting and packing problems).
One common restriction in cutting problems is that the cuts must be guillotine cuts, i.e., each existing rectangle can be cut only to two smaller rectangles; it is impossible to make L-shapes etc. Obviously, the maximum used area with guillotine cuts might be smaller than the maximum used area without restriction.
My question is: Are there upper and lower bounds on the ratio between the optimal guillotine cut and the optimal general cut?
Related work: Song et al. (2009) describe an algorithm that uses a restricted type of guillotine cuts – twice-guillotine cuts. They prove, using geometric constraints, that the ratio between the maximum twice-guillotine cut to the maximum guillotine cut is bounded by $\frac{6}{7}$. I am looking for a comparable result about the ratio between the maximum guillotine cut to the maximum general cut.