In conventional reorder policies for inventory control, stocks are allowed to fluctuate between two prescribed limits: a lower limit corresponding to a safety stock to guard against runouts, and an upper limit to which the stock is replenished from time to time. Methods have been suggested for computing optimal upper and lower limits for the case of stationary demand patterns. The adoption of two rigid limits for controlling inventories for nonstationary demand patterns, which include trends and seasonal fluctuations, is clearly not satisfactory. Published papers in inventory control rarely devote enough attention to the need for a link between forecasting and a reorder policy. A method is suggested in this paper for computing adaptive control limits based on a forecasting procedure that takes account of seasonal fluctuations and trends. The method has been simulated for inventory models with varying parameters. Invariably it has yielded results which were equal to and usually better than those obtained by the optimal “fixed-limits” method. For example, in the case of a normal demand distribution, and a given level of satisfying demand, the reduction in costs resulting from the adaptive control procedure was found to be well over 30%.