## Step 1: Define the symbolic representation of the problem

Let's denote:
- $x_1$ as the number of premium tickets sold
- $x_2$ as the number of regular tickets sold

The objective is to maximize profit, given that the profit per premium ticket is $50 and the profit per regular ticket is $30. Therefore, the objective function can be represented as $50x_1 + 30x_2$.

## Step 2: Identify the constraints

From the problem description, we have the following constraints:
1. Total tickets sold: $x_1 + x_2 \leq 500$ (since they sell 500 tickets)
2. Minimum premium tickets: $x_1 \geq 100$ (at least 100 tickets are reserved to be premium)
3. Ratio of regular to premium tickets: $x_2 \geq 3x_1$ (at least 3 times as many people prefer regular tickets than premium tickets)
4. Non-negativity: $x_1 \geq 0$ and $x_2 \geq 0$ (number of tickets cannot be negative)

## 3: Symbolic representation in JSON format

```json
{
    'sym_variables': [('x1', 'premium tickets'), ('x2', 'regular tickets')],
    'objective_function': '50*x1 + 30*x2',
    'constraints': [
        'x1 + x2 <= 500',
        'x1 >= 100',
        'x2 >= 3*x1',
        'x1 >= 0',
        'x2 >= 0'
    ]
}
```

## 4: Convert the problem into Gurobi code

```python
import gurobi

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

    # Define variables
    x1 = model.addVar(lb=0, name="premium_tickets", vtype=gurobi.GRB.INTEGER)  # Number of premium tickets
    x2 = model.addVar(lb=0, name="regular_tickets", vtype=gurobi.GRB.INTEGER)  # Number of regular tickets

    # Objective function: Maximize 50*x1 + 30*x2
    model.setObjective(50*x1 + 30*x2, gurobi.GRB.MAXIMIZE)

    # Constraints
    model.addConstr(x1 + x2 <= 500, name="total_tickets")  # Total tickets sold
    model.addConstr(x1 >= 100, name="min_premium_tickets")  # Minimum premium tickets
    model.addConstr(x2 >= 3*x1, name="ratio_regular_to_premium")  # Ratio of regular to premium tickets

    # Solve the model
    model.optimize()

    # Check if the model is optimized
    if model.status == gurobi.GRB.OPTIMAL:
        print("Optimal solution found.")
        print(f"Number of premium tickets: {x1.varValue}")
        print(f"Number of regular tickets: {x2.varValue}")
        print(f"Maximum profit: {50*x1.varValue + 30*x2.varValue}")
    else:
        print("No optimal solution found.")

solve_tourist_attraction_problem()
```