## Problem Description and Symbolic Representation

The problem requires maximizing the objective function: $5.57 \times \text{apple pies} + 6.93 \times \text{potatoes}$.

Subject to the following constraints:
- $9.23 \times \text{apple pies} + 12.35 \times \text{potatoes} \geq 18$
- $8 \times \text{apple pies} - 4 \times \text{potatoes} \geq 0$
- $9.23 \times \text{apple pies} + 12.35 \times \text{potatoes} \leq 53$
- $\text{apple pies}$ must be an integer
- $\text{potatoes}$ can be any real number

## Symbolic Representation

```json
{
    'sym_variables': [('x1', 'apple pies'), ('x2', 'potatoes')],
    'objective_function': '5.57*x1 + 6.93*x2',
    'constraints': [
        '9.23*x1 + 12.35*x2 >= 18',
        '8*x1 - 4*x2 >= 0',
        '9.23*x1 + 12.35*x2 <= 53',
        'x1 >= 0 and x1 is an integer (implicitly handled in Gurobi by setting x1 as an integer variable)',
        'x2 >= 0 (not explicitly stated but assumed non-negative)'
    ]
}
```

## Gurobi Code

```python
import gurobi

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

    # Define variables
    apple_pies = model.addVar(name="apple_pies", vtype=gurobi.GRB.INTEGER)
    potatoes = model.addVar(name="potatoes")

    # Objective function
    model.setObjective(5.57 * apple_pies + 6.93 * potatoes, gurobi.GRB.MAXIMIZE)

    # Constraints
    model.addConstr(9.23 * apple_pies + 12.35 * potatoes >= 18)
    model.addConstr(8 * apple_pies - 4 * potatoes >= 0)
    model.addConstr(9.23 * apple_pies + 12.35 * potatoes <= 53)

    # 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"Potatoes: {potatoes.varValue}")
        print(f"Objective: {model.objVal}")
    elif model.status == gurobi.GRB.INFEASIBLE:
        print("The model is infeasible.")
    else:
        print("The model has a non-optimal status.")

solve_optimization_problem()
```