MIDTERM computer implementation question ( 20 points) Eastinghouse sells air conditioners. The annual demand for air conditioners in each region of the country is as follows: East, 100,000; South, 150,000; Midwest, 110,000; West, 90,000 . Eastinghouse is considering building the air conditioners in four different cities: New York, Atlanta, Chicago, and Los Angeles. The cost of producing an air conditioner in a city and shipping it to a region of the country is given in Table 18. Any factory can produce as many as 150,000 air conditioners per year. The annual fixed cost of operating a factory in each city is given in Table 19. At least 50,000 units of the Midwest demand for air conditioners must come from New York, or at least 50,000 units of the Midwest demand must come from Atlanta. TABLE 18 a. Formulate an IP whose solution will tell Eastinghouse how to minimize the annual cost of meeting demand for air conditioners. b. Construct the excel optimization model and fine the optimal solution c. Construct Lindo optimization model and find the optimal solution MIDTERM computer implementation question ( 20 points) Eastinghouse sells air conditioners. The annual demand for air conditioners in each region of the country is as follows: East, 100,000; South, 150,000; Midwest, 110,000; West, 90,000 . Eastinghouse is considering building the air conditioners in four different cities: New York, Atlanta, Chicago, and Los Angeles. The cost of producing an air conditioner in a city and shipping it to a region of the country is given in Table 18. Any factory can produce as many as 150,000 air conditioners per year. The annual fixed cost of operating a factory in each city is given in Table 19. At least 50,000 units of the Midwest demand for air conditioners must come from New York, or at least 50,000 units of the Midwest demand must come from Atlanta. TABLE 18 a. Formulate an IP whose solution will tell Eastinghouse how to minimize the annual cost of meeting demand for air conditioners. b. Construct the excel optimization model and fine the optimal solution c. Construct Lindo optimization model and find the optimal solution