## Problem Description and Formulation

The problem is an optimization problem with three variables: 'bowls of cereal', 'oranges', and 'bowls of pasta'. The objective is to minimize the function:

\[ 8 \times \text{bowls of cereal} + 3 \times \text{oranges} + 2 \times \text{bowls of pasta} \]

subject to several constraints related to the intake of carbohydrates and calcium from these sources.

## Resources/Attributes

The resources/attributes given are:
- \( r0 \): grams of carbohydrates
  - Upper bound: 108
  - Contributions: 
    - \( x0 \): 6 (bowls of cereal)
    - \( x1 \): 3 (oranges)
    - \( x2 \): 5 (bowls of pasta)
- \( r1 \): milligrams of calcium
  - Upper bound: 132
  - Contributions:
    - \( x0 \): 4 (bowls of cereal)
    - \( x1 \): 4 (oranges)
    - \( x2 \): 1 (bowls of pasta)

## Constraints

1. Carbohydrates from bowls of cereal and bowls of pasta: \( 6x_0 + 5x_2 \geq 21 \)
2. Total carbohydrates: \( 6x_0 + 3x_1 + 5x_2 \geq 34 \)
3. Carbohydrates from bowls of cereal and bowls of pasta: Same as 1.
4. Calcium from bowls of cereal and bowls of pasta: \( 4x_0 + x_2 \geq 37 \)
5. Calcium from bowls of cereal and oranges: \( 4x_0 + 4x_1 \geq 23 \)
6. Calcium from oranges and bowls of pasta: \( 4x_1 + x_2 \geq 34 \)
7. Total calcium: \( 4x_0 + 4x_1 + x_2 \geq 35 \)
8. Total calcium: Same as previous.
9. Carbohydrates from bowls of cereal and bowls of pasta: \( 6x_0 + 5x_2 \leq 48 \)
10. Total carbohydrates: \( 6x_0 + 3x_1 + 5x_2 \leq 73 \)

## Gurobi Code

```python
import gurobi

def optimize():
    # Create a new model
    model = gurobi.Model()

    # Define variables
    bowls_of_cereal = model.addVar(lb=0, name="bowls_of_cereal", vtype=gurobi.GRB.CONTINUOUS)
    oranges = model.addVar(lb=0, name="oranges", vtype=gurobi.GRB.CONTINUOUS)
    bowls_of_pasta = model.addVar(lb=0, name="bowls_of_pasta", vtype=gurobi.GRB.CONTINUOUS)

    # Objective function
    model.setObjective(8 * bowls_of_cereal + 3 * oranges + 2 * bowls_of_pasta, gurobi.GRB.MINIMIZE)

    # Constraints
    model.addConstr(6 * bowls_of_cereal + 5 * bowls_of_pasta >= 21, name="carbohydrates_cereal_pasta")
    model.addConstr(6 * bowls_of_cereal + 3 * oranges + 5 * bowls_of_pasta >= 34, name="total_carbohydrates")
    model.addConstr(4 * bowls_of_cereal + bowls_of_pasta >= 37, name="calcium_cereal_pasta")
    model.addConstr(4 * bowls_of_cereal + 4 * oranges >= 23, name="calcium_cereal_oranges")
    model.addConstr(4 * oranges + bowls_of_pasta >= 34, name="calcium_oranges_pasta")
    model.addConstr(4 * bowls_of_cereal + 4 * oranges + bowls_of_pasta >= 35, name="total_calcium")
    model.addConstr(6 * bowls_of_cereal + 5 * bowls_of_pasta <= 48, name="carbohydrates_cereal_pasta_ub")
    model.addConstr(6 * bowls_of_cereal + 3 * oranges + 5 * bowls_of_pasta <= 73, name="total_carbohydrates_ub")

    # Optimize
    model.optimize()

    # Print solution
    if model.status == gurobi.GRB.OPTIMAL:
        print("Optimal Solution:")
        print(f"Bowls of cereal: {bowls_of_cereal.varValue}")
        print(f"Oranges: {oranges.varValue}")
        print(f"Bowls of pasta: {bowls_of_pasta.varValue}")
        print(f"Objective: {model.objVal}")
    else:
        print("No optimal solution found.")

optimize()
```