To solve the given problem, we first need to convert the natural language description into a symbolic representation. Let's define:

- $x_1$ as the number of regular rate tickets sold,
- $x_2$ as the number of concession rate tickets sold.

The objective is to maximize profit. Given that a profit of $2 is made on each regular rate ticket and a profit of $0.50 is made on each concession rate ticket, the objective function can be represented as:

\[ \text{Maximize:} \quad 2x_1 + 0.5x_2 \]

The constraints based on the problem description are:

1. The ferry can carry at most 120 people:
\[ x_1 + x_2 \leq 120 \]
2. At least 15 tickets are reserved for concession rate:
\[ x_2 \geq 15 \]
3. At least 5 times as many tickets sold are regular rate tickets than concession rate tickets:
\[ x_1 \geq 5x_2 \]
4. Non-negativity constraints, since the number of tickets cannot be negative:
\[ x_1 \geq 0, \quad x_2 \geq 0 \]

Thus, the symbolic representation of the problem is:

```json
{
    'sym_variables': [('x1', 'number of regular rate tickets sold'), ('x2', 'number of concession rate tickets sold')],
    'objective_function': '2*x1 + 0.5*x2',
    'constraints': ['x1 + x2 <= 120', 'x2 >= 15', 'x1 >= 5*x2', 'x1 >= 0', 'x2 >= 0']
}
```

Now, let's implement this problem using Gurobi in Python:

```python
from gurobipy import *

# Create a model
m = Model("Ferry_Ticket_Sales")

# Define variables
x1 = m.addVar(lb=0, vtype=GRB.CONTINUOUS, name="regular_rate_tickets")
x2 = m.addVar(lb=0, vtype=GRB.CONTINUOUS, name="concession_rate_tickets")

# Set the objective function
m.setObjective(2*x1 + 0.5*x2, GRB.MAXIMIZE)

# Add constraints
m.addConstr(x1 + x2 <= 120, "total_capacity")
m.addConstr(x2 >= 15, "concession_min")
m.addConstr(x1 >= 5*x2, "regular_rate_proportion")
m.addConstr(x1 >= 0, "non_negative_regular")
m.addConstr(x2 >= 0, "non_negative_concession")

# Optimize the model
m.optimize()

# Print the results
if m.status == GRB.OPTIMAL:
    print("Optimal solution found:")
    print(f"Regular rate tickets: {x1.x}")
    print(f"Concession rate tickets: {x2.x}")
    print(f"Maximum profit: {m.objVal}")
else:
    print("No optimal solution found")
```