SummaryThis paper compares the cost-effectiveness of 4 heuristics to determine the ordering policy in inventory systems with dynamic stochastic demand. The Least Unit Coot method, Part Period balancing, the Silver Meal Algorithm and the Wagner-Whitin Algorithm were adjusted for the stochastic demand case, whereafter their performance was simulated over a 24 period horizon. Also in a stochastic environment the Uagner-Whitin Algorithm turned out to result in significantly lower total costs than the other heuristics.