In the warehouse of a large cosmetics company, a mechanized order picker is restocked from nearby shelving, and the shelving is restocked from bulk storage, forming a three-tier inventory system. We consider such multi-tier inventory systems and determine the storage areas to which to assign items, and the quantities in which to store them, in order to minimize the total cost of picking items and restocking storage locations. With this research, we increase the number of inventory systems for which simple search algorithms find a provably near-optimal solution. The model and method were tested on data from the Avon Products distribution center outside Atlanta; the solution identified by the model reduced picking and restocking costs there by 20%. The sales forecasts of items stored in the warehouse may change, however, and new items will be introduced into the inventory system and others removed. To account for these changes, some warehouses may periodically reassign items to storage areas and recompute their storage quantities. These reassignment activities account for additional costs in the warehouse. The second focus of this research examines these costs over several time periods in a simple multi-tier inventory system. We develop heuristics to determine the storage areas to which to assign items and the quantities in which to store them in each time period, in order to minimize the total cost of picking items, restocking storage locations, and reassigning skus over multiple periods.