Robust Inventory Management Using Tractable Replenishment Policies

We propose tractable replenishment policies for a multi-period, single product inventory control problem under ambiguous demands, that is, only limited information of the demand distributions such as mean, support and deviation measures are available. We obtain the parameters of the tractable replenishment policies by solving a deterministic optimization problem in the form of second order cone optimization problem (SOCP). Our framework extends to correlated demands and is developed around a factor-based model, which has the ability to incorporate business factors as well as time series forecast effects of trend, seasonality and cyclic variations. Computational results show that with correlated demands, our model outperforms a state independent base-stock policy derived from dynamic programming and an adaptive myopic policy. ∗Department of Industrial and Systems Engineering, National University of Singapore. Email: see [email protected] †NUS Business School, National University of Singapore and Singapore MIT Alliance (SMA). Email: [email protected]. The research of the author is supported by SMA, NUS Risk Management Institute and NUS academic research grants R-314-000-066-122 and R-314-000-068-122.