  This paper extends the single-item single-stocking location non-stationary
stochastic inventory problem to relax the assumption of independent demand. We
present a mathematical programming-based solution method that relaxes the
assumption of demand independence between time periods in an existing piecewise
linear approximation strategy under the receding horizon control framework. Our
method can be solved via off-the-shelf mixed-integer linear programming
solvers. It can tackle demand under various assumptions: the multivariate
normal distribution, a collection of time-series processes, and the Martingale
Model of Forecast Evolution. We compare against solutions via stochastic
dynamic programming to demonstrate that our method leads to near-optimal
solutions.
