## Step 1: Define the optimization problem and identify the variables, objective function, and constraints.
The problem requires maximizing the objective function $2.4x_0 + 2.19x_1 + 6.37x_2$, where $x_0$ represents the number of rotisserie chickens, $x_1$ represents the number of ham sandwiches, and $x_2$ represents the quantity of potatoes.

## 2: List the constraints based on the given resources and attributes.
The constraints are as follows:
- $15x_0 + 6x_1 + 15x_2 \geq 28$ (calcium from all sources)
- $17x_1 + 21x_2 \geq 25$ (fat from ham sandwiches and potatoes)
- $20x_0 + 21x_2 \geq 38$ (fat from rotisserie chickens and potatoes)
- $20x_0 + 17x_1 + 21x_2 \geq 35$ (total fat)
- $5x_0 + 14x_1 \geq 13$ (carbohydrates from rotisserie chickens and ham sandwiches)
- $14x_1 + 8x_2 \geq 14$ (carbohydrates from ham sandwiches and potatoes)
- $5x_0 + 8x_2 \geq 14$ (carbohydrates from rotisserie chickens and potatoes)
- $15x_0 + 6x_1 \leq 40$ (calcium from rotisserie chickens and ham sandwiches)
- $15x_0 + 6x_1 + 15x_2 \leq 40$ is not a constraint but $15x_0 + 6x_1 + 15x_2 \leq 122$ (calcium upper bound)
- $17x_1 + 21x_2 \leq 77$ (fat from ham sandwiches and potatoes)
- $20x_0 + 17x_1 \leq 105$ (fat from rotisserie chickens and ham sandwiches)
- $20x_0 + 21x_2 \leq 114$ (fat from rotisserie chickens and potatoes)
- $20x_0 + 17x_1 + 21x_2 \leq 114$ (total fat upper bound, but we have 143 as upper bound)
- $5x_0 + 14x_1 \leq 63$ (carbohydrates from rotisserie chickens and ham sandwiches)
- $14x_1 + 8x_2 \leq 60$ (carbohydrates from ham sandwiches and potatoes)
- $5x_0 + 14x_1 + 8x_2 \leq 60$ (total carbohydrates)

## 3: Correct and consolidate constraints for clarity and accuracy.
Correcting and consolidating:
- Calcium constraints: $28 \leq 15x_0 + 6x_1 + 15x_2 \leq 122$
- Fat constraints: $35 \leq 20x_0 + 17x_1 + 21x_2 \leq 143$
- Specific fat constraints:
  - $17x_1 + 21x_2 \geq 25$
  - $20x_0 + 21x_2 \geq 38$
- Carbohydrate constraints:
  - $13 \leq 5x_0 + 14x_1$
  - $14 \leq 14x_1 + 8x_2$
  - $14 \leq 5x_0 + 8x_2$
  - $5x_0 + 14x_1 \leq 63$
  - $14x_1 + 8x_2 \leq 60$
  - $5x_0 + 14x_1 + 8x_2 \leq 60$

## 4: Write down the Gurobi code for the optimization problem.
```python
import gurobi

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

    # Define variables
    x0 = model.addVar(name="rotisserie_chickens", lb=0)  # Non-negative
    x1 = model.addVar(name="ham_sandwiches", lb=0)    # Non-negative
    x2 = model.addVar(name="potatoes", lb=0)        # Non-negative

    # Objective function
    model.setObjective(2.4 * x0 + 2.19 * x1 + 6.37 * x2, gurobi.GRB.MAXIMIZE)

    # Constraints
    model.addConstr(15 * x0 + 6 * x1 + 15 * x2 >= 28)  # Calcium total minimum
    model.addConstr(15 * x0 + 6 * x1 + 15 * x2 <= 122) # Calcium total upper bound

    model.addConstr(17 * x1 + 21 * x2 >= 25)  # Fat from ham sandwiches and potatoes
    model.addConstr(20 * x0 + 21 * x2 >= 38)  # Fat from rotisserie chickens and potatoes
    model.addConstr(20 * x0 + 17 * x1 + 21 * x2 >= 35)  # Total fat minimum
    model.addConstr(20 * x0 + 17 * x1 + 21 * x2 <= 143) # Total fat upper bound

    model.addConstr(5 * x0 + 14 * x1 >= 13)  # Carbohydrates from rotisserie chickens and ham sandwiches
    model.addConstr(14 * x1 + 8 * x2 >= 14)  # Carbohydrates from ham sandwiches and potatoes
    model.addConstr(5 * x0 + 8 * x2 >= 14)   # Carbohydrates from rotisserie chickens and potatoes
    model.addConstr(5 * x0 + 14 * x1 <= 63)  # Carbohydrates from rotisserie chickens and ham sandwiches upper bound
    model.addConstr(14 * x1 + 8 * x2 <= 60)  # Carbohydrates from ham sandwiches and potatoes upper bound
    model.addConstr(5 * x0 + 14 * x1 + 8 * x2 <= 60)  # Total carbohydrates upper bound

    model.addConstr(15 * x0 + 6 * x1 <= 40)  # Calcium from rotisserie chickens and ham sandwiches upper bound

    model.addConstr(17 * x1 + 21 * x2 <= 77)  # Fat from ham sandwiches and potatoes upper bound
    model.addConstr(20 * x0 + 17 * x1 <= 105) # Fat from rotisserie chickens and ham sandwiches upper bound
    model.addConstr(20 * x0 + 21 * x2 <= 114) # Fat from rotisserie chickens and potatoes upper bound

    # Optimize
    model.optimize()

    # Print solution
    if model.status == gurobi.GRB.OPTIMAL:
        print("Objective: ", model.objVal)
        print("Rotisserie chickens: ", x0.varValue)
        print("Ham sandwiches: ", x1.varValue)
        print("Potatoes: ", x2.varValue)
    else:
        print("No optimal solution found")

optimize_problem()
```