SOLUTION: In order to ensure optimal health, a lab technician needs to feed the rabbits a daily diet containing a minimum of 24 grams (g) of fat, 36 g of carbohydrates, and 4 g of protein. B

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Question 1186926: In order to ensure optimal health, a lab technician needs to feed the rabbits a daily diet containing a minimum of 24 grams (g) of fat, 36 g of carbohydrates, and 4 g of protein. But the rabbits should be fed no more than five ounces of food a day.
Rather than order rabbit food that is custom-blended, it may be cheaper to order Rabbit-Gro and Lucky-Rabbit, and blend them for an optimal mix. Rabbit-Gro contains 8 g of fat, 12 g of carbohydrates, and 2 g of protein per ounce, and costs $0.20 per ounce. Lucky-Rabbit contains 12 g of fat, 12 g of carbohydrates, and 1 g of protein per ounce, at a cost of $0.30 per ounce.

Found 2 solutions by CPhill, ikleyn:
Answer by CPhill(1959) About Me  (Show Source):
You can put this solution on YOUR website!
To determine the most cost-effective mix of Rabbit-Gro and Lucky-Rabbit food that meets the rabbits' nutritional needs, we can use a system of inequalities and solve for the optimal amounts of each food.
**Let:**
* x = ounces of Rabbit-Gro
* y = ounces of Lucky-Rabbit
**Objective:** Minimize cost: C = 0.20x + 0.30y
**Constraints:**
* **Fat:** 8x + 12y ≥ 24
* **Carbohydrates:** 12x + 12y ≥ 36
* **Protein:** 2x + y ≥ 4
* **Total Food:** x + y ≤ 5
* **Non-negativity:** x ≥ 0, y ≥ 0
**Solving the Problem:**
One way to solve this is graphically. Plot each inequality on a graph with x and y axes. The feasible region is where all inequalities are satisfied. The optimal solution will be at one of the vertices (corners) of this region.
Alternatively, you can use linear programming techniques (like the simplex method or software tools) to find the optimal solution.
**Graphical Method (Sketch):**
1. **Plot the lines:** Treat each inequality as an equation and plot the lines on a graph.
2. **Shade the regions:** Shade the appropriate side of each line based on the inequality sign.
3. **Identify the feasible region:** The feasible region is where all shaded areas overlap.
4. **Find the vertices:** Determine the coordinates of the vertices of the feasible region.
5. **Evaluate the objective function:** Plug the x and y coordinates of each vertex into the cost equation (C = 0.20x + 0.30y).
6. **Optimal solution:** The vertex that yields the lowest cost is the optimal solution.
**Linear Programming:**
Linear programming is a more efficient way to solve this type of optimization problem, especially if there are many variables or constraints.
**Expected Outcome:**
By solving the system of inequalities and minimizing the cost function, you'll find the optimal number of ounces of Rabbit-Gro and Lucky-Rabbit to feed the rabbits while meeting their nutritional requirements and staying within the 5-ounce limit.
*The solution will likely involve a combination of both foods, but it's possible that one food alone might be the most cost-effective option.*

Answer by ikleyn(52788) About Me  (Show Source):
You can put this solution on YOUR website!
.
In order to ensure optimal health, a lab technician needs to feed the rabbits a daily diet
containing a minimum of 24 grams (g) of fat, 36 g of carbohydrates, and 4 g of protein.
But the rabbits should be fed no more than five ounces of food a day.

Rather than order rabbit food that is custom-blended, it may be cheaper to order Rabbit-Gro and Lucky-Rabbit,
and blend them for an optimal mix. Rabbit-Gro contains 8 g of fat, 12 g of carbohydrates,
and 2 g of protein per ounce, and costs $0.20 per ounce. Lucky-Rabbit contains 12 g of fat,
12 g of carbohydrates, and 1 g of protein per ounce, at a cost of $0.30 per ounce.
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As I read this problem,  I see that it has a huge  highlight%28highlight%28TRAP%29%29,  and the @PChill' solution falls entirely into this trap.

The trap is that part of masses restrictions in the problem is given in ounces,
while the other part of masses is given in grams.

An accurate solution should make an appropriate/(a necessary) conversion,  but this
Artificial  Intelligence did not notice the trap and fell into it.

Here,  I will not make corrections and improvements - to me,  it is enough to point / (to detect) this deficiency/fault.