Inventory control for a perishable product with non-stationary demand

Globally, around one-third of the edible parts of perishable food products is wasted every year. Adequate logistics management of the food supply chain is of importance. Inventory control of processed fresh food with a best-before or use-by date deals with the questions how much to order and how often, and how to review the inventory position. For perishable products, there exists a trade-off between desired product-availability and waste. A high order quantity or frequent ordering may result in high product-availability but also waste. A small order quantity or less frequent ordering results in lower inventory levels, but may cause out-of-stock. For the inventory control of a perishable product the age-distribution of the items should be considered. This is influenced by order picking at a food producer or warehouse, or consumer behaviour at a supermarket, picking First In First Out (FIFO), where first the oldest items are used, or Last In First Out (LIFO), where first the freshest items of the product are used. This thesis investigates periodic review order policies for a food producer and a retailer for a perishable product with a fixed lifetime and a non-stationary demand. For a food producer as well as a retailer, it is not always economically feasible to reorder in every period. For planning purposes it is desirable to set the timing of the orders in advance. The aim of this thesis is to contribute to better decision making regarding inventory control in the food supply chain from food producer to supermarket, in the trade-off between product-availability and waste. Methods are designed to generate practical order policies using commercial solvers for business rather than custom made solution procedures, where at least the timing of ordering or production is set beforehand. The practical inventory control problems discussed in this thesis are characterised by a perishable product with a fixed lifetime, non-stationary stochastic demand, a single-echelon production/inventory situation in a finite time horizon. The product has a service level requirement to ensure a certain product-availability. The decision problems deal with fixed setup or ordering cost, holding cost and disposal cost for wasted items. The age-distribution of the items in stock is considered in specific theoretical Stochastic Programming (SP) problems that deal with the service level requirement as a chance constraint or fill rate constraint. The studied problems vary in planning characteristics. Fluctuations in demand combined with fixed setup or ordering costs imply that regular production or ordering is probably not optimal. This situation requires a strategy to deal with the fluctuations. In inventory literature, non-stationary demand for a perishable product with a fixed lifetime is hardly studied, and consequently also strategies to deal with it are little investigated. In this thesis, methods have been designed to generate practical order policies using commercial solvers, where at least the timing of ordering or production is set beforehand. The practical order policies have been benchmarked with custom made solution procedures. The developed practical policies are applicable in the practice of fresh food producers and in retail organisations, on the level of the store, as well as on the level of the distribution centre. An interesting conclusion is that the policies with fixed order timing are hardly more costly than the investigated policy with flexible order timing. The fixed order timing increases the ease of planning. The studied cost functions in the models comprise disposal cost for which the value of the disposal cost in the experiments was varied. The results show that in the models with fixed order timing and corresponding order-up-to levels, increasing the disposal cost can reduce the percentage of waste, maintaining the service level. In setting a (fictitious) value for the disposal cost, one can steer the percentage of waste in determining the order policy, and thus contribute to better decision making in the food supply chain from food producer to supermarket in the trade-off between product-availability and waste.