Abstract: Embodiments herein are directed to determining an expected demand for an item. The specialized computer system can model an impact to an expected demand for the item between a current planning horizon and a next planning horizon, including an estimated leftover demand to be fulfilled during the next planning horizon. As calculated, this leftover demand may be less than an unfulfilled demand from the current planning horizon and may be estimated based at least in part on the unfulfilled demand and on historical leftover demand between planning horizons.

Abstract: Techniques for generating a decision to store units of an item may be provided. The units of the item may be offered from a network-based resource. For example, a first ordering channel and a second ordering channel may be provided to facilitate orders of the item from the network-based resource. The first and second ordering channels may allow random orders and deterministic orders of the item, respectively. Additionally, a value of a look ahead window associated with the second ordering channel may be accessed. The value may shift a time for an automatic generation of a deterministic order. Further, a first loss and a second loss may be computed based on the value. The first and second losses may be associated with losing a random order and losing the deterministic order, respectively. The decision may be generated based at least in part on the first loss and the second loss.

Abstract: Techniques for determining a decision to acquire units of an item to be inventoried may be provided. For example, a demand for an item may be simulated to determine a consumption of a capacity for inventorying the item. A discrepancy between the consumption of the capacity and the capacity may be determined. An opportunity cost associated with the capacity may be updated based at least in part on determining that the discrepancy fails a convergence criterion. The opportunity cost may indicate a value associated with using the capacity. The consumption of the capacity may be simulated based at least in part on the updated opportunity cost. A resulting discrepancy may be determined. If the resulting discrepancy meets the convergence criterion, the decision to acquire the units of the item may be generated based at least in part on the updated opportunity cost.