  We explore efficient optimization of toolpaths based on multiple criteria for
large instances of 3D printing problems. We first show that the minimum turn
cost 3D printing problem is NP-hard, even when the region is a simple polygon.
We develop SFCDecomp, a space filling curve based decomposition framework to
solve large instances of 3D printing problems efficiently by solving these
optimization subproblems independently. For the Buddha model, our framework
builds toolpaths over a total of 799,716 nodes across 169 layers, and for the
Bunny model it builds toolpaths over 812,733 nodes across 360 layers. Building
on SFCDecomp, we develop a multicriteria optimization approach for toolpath
planning. We demonstrate the utility of our framework by maximizing or
minimizing tool path edge overlap between adjacent layers, while jointly
minimizing turn costs. Strength testing of a tensile test specimen printed with
tool paths that maximize or minimize adjacent layer edge overlaps reveal
significant differences in tensile strength between the two classes of prints.
