Inventory optimization for perishables subject to supply disruptions

We study a retailer selling perishable products with fixed lifetime. The retailer’s supply system is subject to random disruptions. Assuming a base-stock policy, deterministic demand and stationary cost parameters, we determine the expression for the optimal base-stock level. We show that if the retailer manages to make the system safer, it is possible to operate with the same expected cost even with products with shorter lifetimes. We conclude that the retailer should concentrate on reducing disruptions’ durations instead of their occurrence rate.</p

Optimization of Inventory and Capacity in Large-Scale Assembly Systems Using Extreme-Value Theory

High-tech systems are typically produced in two stages: (1) production of components using specialized equipment and staff and (2) system assembly/integration. Component production capacity is subject to fluctuations, causing a high risk of shortages of at least one component, which results in costly delays. Companies hedge this risk by strategic investments in excess production capacity and in buffer inventories of components. To optimize these, it is crucial to characterize the relation between component shortage risk and capacity and inventory investments. We suppose that component production capacity and produce demand are normally distributed over finite time intervals, and we accordingly model the production system as a symmetric fork-join queueing network with N statistically identical queues with a common arrival process and independent service processes. Assuming a symmetric cost structure, we subsequently apply extreme value theory to gain analytic insights into this optimization problem. We derive several new results for this queueing network, notably that the scaled maximum of N steady-state queue lengths converges in distribution to a Gaussian random variable. These results translate into asymptotically optimal methods to dimension the system. Tests on a range of problems reveal that these methods typically work well for systems of moderate size

Inventory optimization for perishables subject to supply disruptions

We study a retailer selling perishable products with fixed lifetime. The retailer’s supply system is subject to random disruptions. Assuming a base-stock policy, deterministic demand and stationary cost parameters, we determine the expression for the optimal base-stock level. We show that if the retailer manages to make the system safer, it is possible to operate with the same expected cost even with products with shorter lifetimes. We conclude that the retailer should concentrate on reducing disruptions’ durations instead of their occurrence rate