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A pharmaceutical company manufactures two drugs at Los Angeles and Indianapolis. The cost of manufacturing a pound of each drug depends on the location,



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A pharmaceutical company manufactures two drugs at Los Angeles and Indianapolis. The cost of manufacturing a pound of each drug depends on the location, as indicated below. The machine time (in hours) required to produce a pound of each drug at each city is also shown in this table. The company must produce at least 2,000 pounds per week of drug 1 and at least 3,000 pounds per week of drug 2. It has 800 hours per week of machine time at Indianapolis and 600 hours per week at Los Angeles. a. Determine how the company can minimize the cost of producing the required drugs. Total Cost: $ If your answer is zero, enter "0". Production schedule Indianapolis Los Angeles Drug 1 Drug 2 b. Use SolverTable to determine how much the company would be willing to pay to purchase a combination of A extra hours of machine time at Indianapolis and B extra hours of machine time at Los Angeles, where A and B can be any positive multiples of 10 up to 50. Round your answer to the nearest cent and if your answer is zero, enter "0". Indianapolis Los Angeles S $ S $ 1)Inputs are provided in blue. 2)Enter appropriate formulas in blocked cells. 3)Run solver to minimize costs by changing the production schedule subject to constraints. Use Simplex LP method. 4)Run solver table to determine how much the company would be willing to pay for additional hours. Do a two way table using extra hours from Indianpolis and Los Angeles as the input cells. Remember to consider additional costs on a per unit basis. ** Pharmaceutical manufacturing Unit costs Machine requirements Indianapolis.os Angeles Drug 1 $3.80 Drug 2 $4.70 $4.00 $5.20 Indianapolis.os Angeles 0.20 0.24 0.30 0.33 Production schedule Indianapolis.os Angeles Drug 1 0 0 Drug 2 0.0 0.0 Constraints on production Total produced Total required Drug 1 Drug 2 ^^ >= 2000 >= 3000 Constraint on machine time Indianapolis.os Angeles Hours used Hours available Objective to minimize Total cost Original hours available

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