## Problem Description and Formulation

The problem is an optimization problem where we need to maximize the objective function:

1.42 * (number of apple pies) + 8.78 * (quantity of cantaloupes)

subject to several constraints related to the nutritional content of apple pies and cantaloupes.

## Constraints

1. Apple pies contain 3.47 milligrams of calcium.
2. Cantaloupes contain 0.49 milligrams of calcium.
3. The total calcium from both sources must be at least 19 milligrams but no more than 30 milligrams.
4. Apple pies contain 4.7 milligrams of iron.
5. Cantaloupes contain 3.14 milligrams of iron.
6. The total iron from both sources must be at least 23 milligrams but no more than 28 milligrams.
7. Apple pies contain 5.64 grams of protein.
8. Cantaloupes contain 1.53 grams of protein.
9. The total protein from both sources must be at least 7 grams but no more than 26 grams.
10. 3 times the number of apple pies minus 9 times the number of cantaloupes must be greater than or equal to zero.

## Gurobi Code Formulation

```python
import gurobi

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

    # Define variables
    apple_pies = model.addVar(name="apple_pies", lb=0, ub=gurobi.GRB.INFINITY, vtype=gurobi.GRB.CONTINUOUS)
    cantaloupes = model.addVar(name="cantaloupes", lb=0, vtype=gurobi.GRB.INTEGER)

    # Objective function
    model.setObjective(1.42 * apple_pies + 8.78 * cantaloupes, gurobi.GRB.MAXIMIZE)

    # Constraints
    # Calcium constraints
    model.addConstr(3.47 * apple_pies + 0.49 * cantaloupes >= 19, name="calcium_min")
    model.addConstr(3.47 * apple_pies + 0.49 * cantaloupes <= 30, name="calcium_max")

    # Iron constraints
    model.addConstr(4.7 * apple_pies + 3.14 * cantaloupes >= 23, name="iron_min")
    model.addConstr(4.7 * apple_pies + 3.14 * cantaloupes <= 28, name="iron_max")

    # Protein constraints
    model.addConstr(5.64 * apple_pies + 1.53 * cantaloupes >= 7, name="protein_min")
    model.addConstr(5.64 * apple_pies + 1.53 * cantaloupes <= 26, name="protein_max")

    # Additional constraint
    model.addConstr(3 * apple_pies - 9 * cantaloupes >= 0, name="additional_constraint")

    # Solve the model
    model.optimize()

    # Print the solution
    if model.status == gurobi.GRB.OPTIMAL:
        print("Optimal solution found.")
        print(f"Apple pies: {apple_pies.varValue}")
        print(f"Cantaloupes: {cantaloupes.varValue}")
        print(f"Objective: {model.objVal}")
    else:
        print("No optimal solution found.")

solve_optimization_problem()
```