Inventory Management of Perishable Goods under Demand Variability

Perishability of fluid milk presents challenges for efficient distribution and limits market expansion for dairy when temperatures cannot be fully controlled during transportation. This research develops a modeling framework that integrates food science and economic parameters examining the impacts of different demand specifications on the cost minimization and profit maximization problem of fluid milk. The square root model from the food science literature is used to estimate the shelf-life of fluid milk at retail level. The shelf-life parameter is then used as input to the fixed- order quantity inventory model from the business economic literature. Additionally two demand specifications, the own-price elasticity and the negative binomial distribution, are used to calculate the total cost of managing inventory and resulting profit.

Modeling results confirm that fluctuations in temperature and time dramatically increase the percentage of perishability cost and decrease profitability. Specifications of retail demand directly impact outcomes of the inventory model. Under the demand model based on price elasticity, simulated total costs are lower and profits are higher than under the negative binomial specification. The negative binomial distribution approach provides a simulated outcome where sales losses are minimized and customer satisfaction is higher. This thesis proposes, presents and uses a working model that can be extended and directly applied for fluid milk as well as other perishable food supplies.