# Operations Decision

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Submitted By jazzy3js
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Pages 3
Chapter 5 Problems 1, 5, 6 & 9

1. a. S = k(YZ)/P S= 100(11,000 x 1200)/20,000=66,000

b. S=100(11,000 x 1200)/17,500=75429

c. If you would get the data time series for S, Y, Z, & P, use the regression methods to guess k.

d. The sales that are in period t are a function of variables whose values are unknown prior to period t. Before you could guess St, Yt, Zt and Pt would have to be guessed first.

5.
Year Demand 5yr MA 3 yr MA Exp Smo(w=9) Exp Smo(w=3)
1995 800
1996 925 800 800
1997 900 912.50 837.50
1998 1025 875 901.25 856.25
1999 1150 950 1012.62 906.87
2000 1160 960 1025 1136.26 979.81
2001 1200 1032 1112 1157.63 1033.87
2002 1150 1087 1170 1195.76 1083.71
2003 1270 1137 1170 1154.58 1103.59
2004 1290 1186 1207 1258.46 1153.51
2005 1214 1237 1286.85 1194.45

b. RMSE = [Σ(Yact − Yest)2/n].5 Five-year moving average = (100,698/5).5 = 141.9 Three-year moving average = (43,258/7).5= 78.6 Exponential smoothing (w = .9) = (18,769/9).5 = 45.7 Exponential smoothing (w = .3) = (110,783.79/9).5 = 110.9

c. According to the RMSE standard, the exponential smoothing (w = .9) forecast for 19Y0 is preferred. The data support an exponential forecast with a trend factor.

6.
a. QD = 18,000+0.4(15,000)-350(50) +90(55) =11,450

b. QD = 18,000+0.4(15,000)-350(50) +90(50) =11,000

c. QD = 18,000+0.4(10,500)-350(50) +90(55) =9,650

9. Quarter 1 2010: t =21: D11=1 D21= 0 D31=0 Y'1 = 8.25 + .125(21) − 2.75(1) + 0.25(0) + 3.50(0) = \$8.125 (million)
Quarter 2 2010: t =22: D12=1 D22= 0 D32=0 Y'1 = 8.25 + .125(22) − 2.75(1) + 0.25(0) + 3.50(0) = \$13.25 (million)
Quarter 2 2010: t =23: D13=1 D23= 0 D33=0 Y'1 = 8.25 + .125(23) − 2.75(1) + 0.25(0) + 3.50(0) = \$14.625 (million)
Quarter 2 2010: t =24: D14=1 D24= 0 D34=0 Y'1 = 8.25 + .125(24) −

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