  We consider the dynamic inventory problem with non-stationary demands. It has
long been known that non-stationary (s, S) policies are optimal for this
problem. However, finding optimal policy parameters remains a computational
challenge as it requires solving a large-scale stochastic dynamic program. To
address this, we devise a recursion-free approximation for the optimal cost
function of the problem. This enables us to compute policy parameters
heuristically, without resorting to a stochastic dynamic program. The heuristic
is easy-to-understand and -use since it follows by elementary methods of convex
minimization and shortest paths, yet it is very effective and outperforms
earlier heuristics.
