B. This problem explores the solution of linear programs with MATLAB. We are given the following optimization problem The Trail Mix made by the Beta Beta food market contains at least 40% of cashews and at most 25% of peanuts. The food market can package no more than 100 pounds of mix per week and there are 40 pounds of peanuts, 25 pounds of almonds and 20 pounds of cashews available. If the costs per pound are: peanuts: $2.00 almonds: $3.50, cashews: $5.00 and the trail mix sells for $8.00 per pound, how do they maximize profit? We introduce three variables, p, a, and c, representing the amounts of peanuts, monds, and cashews to be used to prepare the Trail Mix every week. Clearly, all these amounts must be non-negative. Hence we have lower bounds of 0 for all three. The problem description also gives us upper bounds for each type of nut. Next we turn to the constraints on the percentages. For the peanuts and cashews, we can write p 0.25(pac) 0.4(p+a+c B. This problem explores the solution of linear programs with MATLAB. We are given the following optimization problem The Trail Mix made by the Beta Beta food market contains at least 40% of cashews and at most 25% of peanuts. The food market can package no more than 100 pounds of mix per week and there are 40 pounds of peanuts, 25 pounds of almonds and 20 pounds of cashews available. If the costs per pound are: peanuts: $2.00 almonds: $3.50, cashews: $5.00 and the trail mix sells for $8.00 per pound, how do they maximize profit? We introduce three variables, p, a, and c, representing the amounts of peanuts, monds, and cashews to be used to prepare the Trail Mix every week. Clearly, all these amounts must be non-negative. Hence we have lower bounds of 0 for all three. The problem description also gives us upper bounds for each type of nut. Next we turn to the constraints on the percentages. For the peanuts and cashews, we can write p 0.25(pac) 0.4(p+a+c