Weighted Moving Averages In the sim

Weighted Moving Averages In the simple moving average method, each demand has the same weightin the average—namely, 1>n. In the weighted moving average method, each historical demand in the average can have its own weight. The sum of the weights equals 1.0. For example, in a three-period weighted moving average model, the most recent period might be assigned a weight of 0.50, the second most recent might be weighted 0.30, and the third most recent might be weighted 0.20. The average is obtained by multiplying the weight of each period by the value for that period and adding the products together: Ft + 1 = 0.50Dt + 0.30Dt - 1 + 0.20Dt – 2 For a numerical example of using the weighted moving average method to estimate average demand, see Solved Problem 2 and Tutor 8.2 of OM Explorer in MyOMLab. The advantage of a weighted moving average method is that it allows you to emphasize recent demand over earlier demand. (It can even handle seasonal effects by putting higher weights on prior years in the same season.) The forecast will be more responsive to changes in the underlying average of the demand series than the simple moving average forecast.