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A drone manufacturer produces 2 types of drones, the multi-rotor (MR), and the single-rotor (SR). The profit margin is $150 per unit for MR drones

A drone manufacturer produces 2 types of drones, the multi-rotor (MR), and the single-rotor (SR). The profit margin is $150 per unit for MR drones and $200 per unit for SR drones. One assembly machine is used to produce both models, and it operates for 600 minutes each day. An MR unit needs 10 minutes in the assembly machine, and an SR unit needs 30 minutes. The drones also need to be tested, and are both types are tested on the same machine, which operates for 600 minutes each day. An MR unit requires 10 minutes of testing machine time, and an SR unit needs 20 minutes. The last phase of production is packaging, and both products are packaged on the same packaging machine and both drone types takes 20 minutes to pack. Determine the most profitable daily production plan and answer the following questions using the sensitivity report generated by Excel solver only. a) If the packaging machine has 1000 minutes available (instead of 600), how will the optimal solution change? b) If the testing machine has 500 minutes available, by how much will the optimal profit change? c) If the assembly machine has 1000 minutes available, by how much will the optimal profit change? d) If the profit margin for MR is $200 per unit, how will the optimal profit change? How will the optimal decision variables change? e) If the profit margin for SR is $100 per unit, how will the optimal solution change? f) The company is also capable of producing a third type of drone, fixed-wing (FW) drones. FW drones needs 10 minutes for assembly, 20 minutes for testing and 15 minutes for packaging. Based on your existing information (i.e., without reformulating your optimization model), what is the minimum profit contribution per unit for the FW drones that would incent the company to consider producing them in addition to the two existing products? Note: There are 3 separate machines that share the same resource pool

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