A Case History in Optimum Inventory Scheduling

This paper describes four computer programs that perform what were formerly management-decision functions in inventory scheduling. The first program solves the classical EOQ problem (uniform inventory usage) with quantity discounts. The second program, Economic Requirement Batching (ERB), uses dynamic programming, a heuristic search algorithm, and the relation between shipment size and material cost to locate the optimum delivery schedule for any deterministic schedule of discrete (irregular) requirements. The third program, the Alternative Delivery Schedule Evaluator (ADSE), compares any alternative delivery schedules that meet requirements; it calculates all costs associated with inventory and displays both the optimum alternative and the opportunity losses incurred by inferior alternatives. The fourth program, the Alternative Delivery Schedule Generator (ADSG), solves the difficult problem of optimally scheduling inventory in those cases requiring vendor production to special specifications and, accordingly, where the exact price of the item is unknown and depends on the manner in which it is produced. This situation is differentiated from ERB because ERB analyzes standard vendor shelf items that can be delivered according to any schedule. With little input data, ADSG generates a few highly efficient alternative delivery schedules upon which the vendor quotes. The returned bids are then evaluated by ADSE, which determines the optimum delivery schedule. Since over three years have elapsed between when this work was done and the publication of this article, it concludes with a view of the program's successes and failures and some relevant empirically observed relations.