Many supermarkets and retailers use computer assisted ordering (CAO) or automated order systems (ASO) to determine replenishment quantities. Traditionally, these systems are designed for non-perishables, and order quantities are set by (modified) base stock policies, determined according to the total number of units in stock, regardless of the ages of the products in stock. Today's technology allows the user to keep track of the age of inventories. In the last decade, a few so-called stock-age dependent order policies have been proposed. An optimal stock-age dependent policy may be computed by stochastic dynamic programming (SDP), but an SDP policy is hardly ever adopted in practice for two reasons: (1) the policy can only be computed if the underlying state space is not too large, and (2) the resulting policy can have a complicated structure. In practice, logistics managers prefer well structured policies they do understand, such as base stock policies (BSP). In this paper, we give an overview of existing stock-age dependent order policies and provide new stock-age dependent order policies. We present a simulation-based search procedure and suggest search ranges for setting optimal parameter values. For a broad set of 11,177 instances, we test the algorithm, compare these policies by simulation, and discuss the value of stock-age information. A new policy, named BSP-low-EW, performs close to optimal (SDP) and turns out to outperform all other policies in virtually all cases.
- Food waste
- Perishable inventory management
- Simulation-based optimization
- Stock-age dependent ordering