Case 1. 
A company must decide now which of three products to make next year to plan and order proper materials. The cost per unit of producing each product will be determined by whether a new union labor contract passes or fails. The cost per unit for each product, given each contract result, is shown in the following payoff table: 
Table 1 .Payoff table for case 1. 
 
Contract Outcome 
 
 
Product 
 
Pass (S1 ) 
 
Fail (S2 ) 
 
 
1(d1 ) 
 
$7.50 
 
$6.00 
 
 
2(d2 ) 
 
4.00 
 
7.00 
 
 
3(d3 ) 
 
6.50 
 
3.00 
 
 
 
Note that this payoff table is for costs. This is minimization problem. Determine which product should be produced, using the following decision criteria. 
 1)use the optimistic approach 
Question 1 options: 
 
select d3
 
 
 
select d1
 
 
 
select d2
 
 
 
non of these alternatives is correct
 
 
 
 case 1(continued)
 use conservative approach
Question 2 options: 
 
select d1
 
 
 
select d2
 
 
 
select d3
 
 
 
non of these alternatives is correct
 
 
 
case 1(continued)
 use minimax regret approach
Question 3 options: 
 
select d2
 
 
 
select d3
 
 
 
select d1
 
 
 
none of these alternatives is correct
 
 
 
 case 1 (continued)
Suppose that the probabilities that a new union labor contract passes (s1 ) is 0.7 and the probabilities that a new union labor contract fails (s2 ) is 0.3.  What option should a company choose using the expected value approach?
Question 4 options: 
 
select d2
 
 
 
select d1
 
 
 
select d3
 
 
 
non of these alternatives is correct
 
 
 
case 1(continued)
 Compute EV(d1 ) 
Question 5 options: 
 
7.05
 
 
 
4.90
 
 
 
5.45
 
 
 
Non of these alternatives is correct
 
 
 
 Case1(continued)
 Compute EV(d2)
Question 6 options: 
 
7.05
 
 
 
5.45
 
 
 
4.90
 
 
 
non of these alternatives is correct
 
 
 
case 1(continued) 
Which equation we should use to compute  
Expected Value of Perfect Information (EVPI) 
Question 7 options: 
 
 EVPI  (EV of  PI) = abs(EV with  PI – EV of our optimal decision)=abs(EVwPI-EVwoPI)
 
 
 
 EVPI=EVwPI-EVwoPI
 
 
 
 EVPI=EVwSI-EVwoSI
 
 
 
non of these alternatives is correct
 
 
 
case 1 (continued)
 Let’s compute EV with PI (EVwPI)
Question 8 options: 
 
3.7
 
 
 
2.2
 
 
 
1.4
 
 
 
non of these alternatives is correct
 
 
 
case 1(continued)
 Compute EVPI
Question 9 options: 
 
-4.9
 
 
 
-2.1
 
 
 
1.2
 
 
 
non of these alternative is correct
 
 
 
Case 2. 
RAP Computers assembles personal computers from generic parts it purchases at discount, and it sells the units by phone orders it receives from customers responding to the company’s ads in trade journals. Actual demand for the company’s computers for the past 6 month is shown in the table below.
 Table 2.  Actual demand for the company’s computers for the past 6 month
# 
 
Month 
 
Demand 
 
 
1
 
March
 
120
 
 
2
 
April
 
110
 
 
3
 
May
 
150
 
 
4
 
June
 
130
 
 
5
 
July
 
160
 
 
6
 
August
 
165
 
 
 
  
Determine
 a three-month moving average forecast for next month (September). 
Question 10 options: 
 Case 2 (continued)
Determine
 a five-month moving average forecast for next month (September). 
Question 11 options: 
case 2(continued)
Compute a weighted three-month average forecast for the next month (September). Assign weights of .55, .33, and .12 to the months in sequence, starting with the most recent month.
Question 12 options: 
Case 2 (continued)
Determine the simple exponential smoothing forecast for next Month (September) using α = .4
Question 13 options: 
 
151.1136≈151
 
 
 
143
 
 
 
151.6
 
 
 
159.15
 
 
 
Table 3  -month moving average forecast
# 
 
Month 
 
Demand 
 
 Forecast 
 
abs(Dt -Ft ) 
 
(Dt -Ft )2  
 
 
1
 
March
 
120
 
 
 
 
 
2
 
April
 
110
 
 
 
 
 
3
 
May
 
150
 
 
 
 
 
4
 
June
 
130
 
126.667
 
3.333333
 
11.1111
 
 
5
 
July
 
160
 
130
 
30
 
900
 
 
6
 
August
 
165
 
146.667
 
18.33333
 
336.111
 
 
 
 
 
 
Sum 
 
Sum 
 
 
 
 
 
 
51.66667
 
1247.22
 
 
 
 case 2(continued)
 Measure the accuracy of the three -month moving average forecast by using MAD. (Use table 3 from Excel).
Question 14 options: 
 
 MAD is 51.66/3=17.222222
 
 
 
 MAD is 51.66/6=8.61
 
 
 
 MAD is 51.66/5=10.332
 
 
 
 MAD is 51.66/455=0.11
 
 
 
case 2(continued)
Measure the accuracy of the three -month moving average forecast by using MAPD. (Use table 3 from Excel).
Table 3 ( 3 -month moving average forecast)
# 
 
Month 
 
Demand 
 
 Forecast 
 
abs(Dt -Ft ) 
 
(Dt -Ft )2  
 
 
1
 
March
 
120
 
 
 
 
 
2
 
April
 
110
 
 
 
 
 
3
 
May
 
150
 
 
 
 
 
4
 
June
 
130
 
126.667
 
3.333333
 
11.1111
 
 
5
 
July
 
160
 
130
 
30
 
900
 
 
6
 
August
 
165
 
146.667
 
18.33333
 
336.111
 
 
 
 
 
 
Sum 
 
Sum 
 
 
 
 
 
 
51.66667
 
1247.22
 
 
 
Question 15 options: 
 
MAPD is
51.66/3*100%=172.2%
 
 
 
MAPD is
51.66/835*100%=6.2%
 
 
 
MAPD is
51.66/455*100%=11.36%
 
 
 
MAPD is 
51.66/6*100%=861%
 
 
 
case 2(continued)
 Measure the accuracy of the three -month moving average forecast by using MSE. (Use table 3. From Excel).
 Table 3.( 3 -month moving average forecast)
# 
 
Month 
 
Demand 
 
 Forecast 
 
abs(Dt -Ft ) 
 
(Dt -Ft )2  
 
 
1
 
March
 
120
 
 
 
 
 
2
 
April
 
110
 
 
 
 
 
3
 
May
 
150
 
 
 
 
 
4
 
June
 
130
 
126.667
 
3.333333
 
11.1111
 
 
5
 
July
 
160
 
130
 
30
 
900
 
 
6
 
August
 
165
 
146.667
 
18.33333
 
336.111
 
 
 
 
 
 
Sum 
 
Sum 
 
 
 
 
 
 
51.66667
 
1247.22
 
 
 
Question 16 options: 
 
MSE is 
1247.22/3≈415.74
 
 
 
MSE is
1247.22/6=207.87
 
 
 
MSE is 
1247.22/455=2.74
 
 
 
1247.22/835=1.5
 
 
 
 Case 2 (continued)
 Measure the accuracy of the weighted three-month average forecast by using MAD. Use table 4.
Table 4 . Weighted three-month average forecast (0.55,.33,.12)
# 
 
Month 
 
Demand 
 
Forecast 
 
ABS(Dt -Ft ) 
 
(Dt -Ft )2  
 
 
1
 
March
 
120
 
 
 
 
 
2
 
April
 
110
 
 
 
 
 
3
 
May
 
150
 
 
 
 
 
4
 
June
 
130
 
133.2
 
3.2
 
10.24
 
 
5
 
July
 
160
 
134.2
 
25.8
 
665.64
 
 
6
 
August
 
165
 
148.9
 
16.1
 
259.21
 
 
  
 
  
 
SUM 
 
  
 
SUM 
 
SUM 
 
 
 
 
455
 
 
45.1
 
935.09
 
 
 
MAD=45.1/3=15.03(3)
Question 17 options: 
 
MAD=45.1/3=15.03(3)
 
 
 
MAD=45.1/6=7.51
 
 
 
MAD=45.1/455=0.0991
 
 
 
non of these alternative is correct
 
 
 
Measure the accuracy of the weighted three-month average forecast by using 
 MAPD. Use table 4.
Table 4 . Weighted three-month average forecast (0.55,.33,.12)
# 
 
Month 
 
Demand 
 
Forecast 
 
ABS(Dt -Ft ) 
 
(Dt -Ft )2  
 
 
1
 
March
 
120
 
 
 
 
 
2
 
April
 
110
 
 
 
 
 
3
 
May
 
150
 
 
 
 
 
4
 
June
 
130
 
133.2
 
3.2
 
10.24
 
 
5
 
July
 
160
 
134.2
 
25.8
 
665.64
 
 
6
 
August
 
165
 
148.9
 
16.1
 
259.21
 
 
  
 
  
 
SUM 
 
  
 
SUM 
 
SUM 
 
 
 
 
455
 
 
45.1
 
935.09
 
 
 
Question 18 options: 
 
 MAPD=45.1/835*100%=5.4%
 
 
 
 MAPD=45.1/455*100%=9.91%
 
 
 
 MAPD=45.1/3=15.03
 
 
 
 MAPD=45.1/6=7.52
 
 
 
case 2 (continued)
Measure the accuracy of the weighted three-month average forecast by using MSE. Use table 4.
 Table 4 . Weighted three-month average forecast (0.55,.33,.12)
# 
 
Month 
 
Demand 
 
Forecast 
 
ABS(Dt -Ft ) 
 
(Dt -Ft )2  
 
 
1
 
March
 
120
 
 
 
 
 
2
 
April
 
110
 
 
 
 
 
3
 
May
 
150
 
 
 
 
 
4
 
June
 
130
 
133.2
 
3.2
 
10.24
 
 
5
 
July
 
160
 
134.2
 
25.8
 
665.64
 
 
6
 
August
 
165
 
148.9
 
16.1
 
259.21
 
 
  
 
  
 
SUM 
 
  
 
SUM 
 
SUM 
 
 
 
 
455
 
 
45.1
 
935.09
 
 
 
Question 19 options: 
 
 MSE=935.09/3≈311.697
 
 
 
 MSE=935.09/6=155.85
 
 
 
 MSE=45.1/455*100%=9.91%
 
 
 
MSE=45.1/3=15.03(3)
 
 
 
Based on your measure the accuracy of the three-month average forecast and the weighted three-month average forecast which of the forecasting methods would you want to rely upon to forecast demand for September?
Question 20 options: 
 
I would prefer the 3-month weighted moving average forecasting method as it has the lowest MAD, lowest MAPD, and lowest MSE.
 
 
 
I would prefer the 3-month moving average forecasting method as it has the lowest MAD, lowest MAPD, and lowest MSE.
 
 
 
I would prefer both of them because they have the same MAD, MAPD, and MSE.
 
 
 
non of these alternatives is correct