  We devise a method to exactly compute the length of the longest simple path
in factored state spaces, like state spaces encountered in classical planning.
Although the complexity of this problem is NEXP-Hard, we show that our method
can be used to compute practically useful upper-bounds on lengths of plans. We
show that the computed upper-bounds are significantly (in many cases, orders of
magnitude) better than bounds produced by previous bounding techniques and that
they can be used to improve the SAT-based planning.
