1) Consider the data in the Excel file Nuclear Power. Use simple linear regression to forecast the data. What would be the forecasts for the next 3 years? File attached. 2) Valencia Products makes automobile radar detectors and assembles two models: Laser Stop and Speed Buster. The firm can sell all it produces. Both models use the same electronic components. Two of these can be obtained only from a single supplier. For the next month, the supply of these is limited to 4,000 of component A and 3,500 of component B. The number of each component required for each product and the profit per unit are given in the table. Components Components Required/Unit LaserStop SpeedBuster A 18 12 B 6 10 Profit/unit $24 $40 a) Identify the decision variables, objective function, and constraints in simple verbal statements. b) Mathematically formulate a linear optimization model. 3) Implement the linear optimization model that you developed for Valencia Products in the last problem in Excel and use Solver to find an optimal solution. Interpret the Solver Answer report and identify the binding constraints and verify the values of the slack variables by substituting the optimal solution into the model constraints. Nuclear Electric Power Production (Billion KWH) Year US Canada France 1980 251.12 35.88 63.42 1981 272.67 37.8 99.24 1982 282.77 36.17 102.63 1983 293.68 46.22 135.99 1984 327.63 49.26 180.47 1985 383.69 57.1 211.19 1986 414.04 67.23 239.56 1987 455.27 72.89 249.27 1988 526.97 78.18 260.29 1989 529.35 75.35 288.72 1990 576.86 69.24 298.38 1991 612.57 80.68 314.77 1992 618.78 76.55 321.52 1993 610.29 90.08 349.78 1994 640.44 102.44 341.98 1995 673.4 92.95 358.37 1996 674.73 88.13 377.47 1997 628.64 77.86 375.71 1998 673.7 67.74 368.59 1999 728.25 69.82 374.53 2000 753.89 69.16 394.4 2001 768.83 72.86 400.02 2002 780.06 71.75 414.92 2003 763.73 71.15 419.02 2004 788.53 85.87 425.83 2005 781.99 87.44 428.95 2006 787.22 93.07 427.68