An airplane manufacturer specializes in producing small airplanes. It has just received an order from a major corporation for 10 customized executive jet airplanes for the use of the corporation's upper management. The order calls for three of the airplanes to be delivered (and paid for) during the upcoming winter months (period 1), two more to be delivered during the spring (period 2), three more during the summer (period 3), and the final two during the fall (period 4). Setting up the production facilities to meet the corporation's specifications for these airplanes requires a setup cost of $2 million. The manufacturer has the capacity to produce all 10 airplanes within a couple of months, when the winter season will be under way. However, this would necessitate holding seven of the airplanes in inventory, at a cost of $200,000 per airplane per period, until their scheduled delivery times. To reduce or eliminate these substantial holding costs, it may be worthwhile to produce a smaller number of these airplanes now and then to repeat the setup (again incurring the cost of $2 million) in some or all of the subsequent periods to produce additional small numbers. Management would like to determine the least costly production schedule for filling this order Thus, using the notation of the model, the demands for this particular airplane during the four upcoming periods (seasons) are r1-3, r2 2, r3 - 3, r4- 2. Using units of millions of dollars, the relevant costs are K-2, h-0.2. The cost for producing each airplane varies from period to period. In either period 1 or period 3, the cost is 1.4 million dollars per plane. In either period 2 or 4, the cost is only 1 million dollars per plane. Use Dynamic programming to determine how many airplanes (if any) should be produced in each of the four periods to minimize total cost