Inventory optimization (IO) is a strategy for balancing the amount of working capital that's tied up in inventory with service-level goals across multiple stock-keeping units (SKUs).
Modeling tools for inventory optimization can be deterministic or stochastic. In a deterministic inventory optimization model, each set of variables is known. In the stochastic inventory optimization model, the variables are described by probability distributions.
The stochastic approach, which requires a computer to calculate numerous random input variables within an acceptable timeframe, is considered to be the more accurate of the two approaches because it is designed to take supply chain uncertainty and the volatility of demand into account.