Exam 21: Operational Decison-Making Tools: Transportation and Transshipment Models

For the demand values and the January forecast shown in the table below the exponential smoothing forecast for March using α = 0.40 is

Forecasts of product demand determine how much

A forecasting model has produced the following forecasts: At the end of May the tracking signal would be

The per-period average of cumulative error is called

Given the demand and forecast values shown in the table below, the mean absolute deviation (MAD) through the end of October is

Exponential smoothing is an averaging method for forecasting that reacts more strongly to recent changes in demand.

(Use the following information for the next five problems.) The owner of Koffi, the sole coffee house located in a resort area, wants to develop a forecast based on the relationship between tourism and coffee drinks sold. He has generated the following data over the past 12 months: The data from using Data Analysis on Excel is as follows: -What is the approximate slope, b?

The type of forecasting method selected depends on time frame, demand behavior, and causes of behavior.

Time series methods assume that demand patterns in the past are a good predictor of demand in the future.

A tracking signal is computed by

Given the demand and forecast values shown in the table below, the forecast error for September is

If the forecast for July was 3,300 and the actual demand for July was 3,250, then the exponential smoothing forecast for August using α = 0.20 is

The type of forecasting method selected depends on time frame, demand behavior and causes of behavior.

A forecasting model has produced the following forecasts, the forecast error for February is

Which of the following is not a type of predictable demand behavior?

The demand behavior for skis is considered cyclical.

Which of the following statements concerning average error is true?

Correlation is a measure of the strength of the

Time series methods use historical data to predict future demand.

The larger the mean absolute deviation (MAD) the more accurate the forecast.