## Step 1: Define the symbolic representation of the variables
The variables are defined as follows: 
- $x_1$ = ravioli
- $x_2$ = cheeseburgers
- $x_3$ = steaks
- $x_4$ = bagged salads
- $x_5$ = hamburgers

## Step 2: Determine the objective function in symbolic notation
The objective function to minimize is $3.66x_1 + 5.55x_2 + 2.59x_3 + 4.16x_4 + 8.57x_5$.

## 3: List the constraints in symbolic notation
The constraints are:
- $18x_1 + 7x_5 \geq 20$
- $18x_1 + 18x_4 \geq 6$
- $17x_3 + 18x_4 \geq 19$
- $17x_3 + 18x_4 + 7x_5 \geq 20$
- $18x_1 + 3x_2 + 17x_3 + 18x_4 + 7x_5 \geq 20$
- $4x_3 - 9x_4 \geq 0$
- $-4x_2 + 3x_3 \geq 0$
- $18x_1 + 7x_5 \leq 38$
- $3x_2 + 7x_5 \leq 91$
- $18x_1 + 3x_2 + 17x_3 \leq 34$
- $x_1$ is an integer
- $x_2$ is an integer
- $x_3$ is continuous
- $x_4$ is an integer
- $x_5$ is an integer

## 4: Create the symbolic representation of the problem
```json
{
    'sym_variables': [
        ('x1', 'ravioli'), 
        ('x2', 'cheeseburgers'), 
        ('x3', 'steaks'), 
        ('x4', 'bagged salads'), 
        ('x5', 'hamburgers')
    ], 
    'objective_function': '3.66*x1 + 5.55*x2 + 2.59*x3 + 4.16*x4 + 8.57*x5', 
    'constraints': [
        '18*x1 + 7*x5 >= 20',
        '18*x1 + 18*x4 >= 6',
        '17*x3 + 18*x4 >= 19',
        '17*x3 + 18*x4 + 7*x5 >= 20',
        '18*x1 + 3*x2 + 17*x3 + 18*x4 + 7*x5 >= 20',
        '4*x3 - 9*x4 >= 0',
        '-4*x2 + 3*x3 >= 0',
        '18*x1 + 7*x5 <= 38',
        '3*x2 + 7*x5 <= 91',
        '18*x1 + 3*x2 + 17*x3 <= 34'
    ]
}
```

## 5: Write the Gurobi code for the optimization problem
```python
import gurobi

# Create a new model
model = gurobi.Model()

# Define the variables
x1 = model.addVar(name="ravioli", vtype=gurobi.GRB.INTEGER)  # integer
x2 = model.addVar(name="cheeseburgers", vtype=gurobi.GRB.INTEGER)  # integer
x3 = model.addVar(name="steaks", vtype=gurobi.GRB.CONTINUOUS)  # continuous
x4 = model.addVar(name="bagged_salads", vtype=gurobi.GRB.INTEGER)  # integer
x5 = model.addVar(name="hamburgers", vtype=gurobi.GRB.INTEGER)  # integer

# Set the objective function
model.setObjective(3.66 * x1 + 5.55 * x2 + 2.59 * x3 + 4.16 * x4 + 8.57 * x5, gurobi.GRB.MINIMIZE)

# Add constraints
model.addConstr(18 * x1 + 7 * x5 >= 20)
model.addConstr(18 * x1 + 18 * x4 >= 6)
model.addConstr(17 * x3 + 18 * x4 >= 19)
model.addConstr(17 * x3 + 18 * x4 + 7 * x5 >= 20)
model.addConstr(18 * x1 + 3 * x2 + 17 * x3 + 18 * x4 + 7 * x5 >= 20)
model.addConstr(4 * x3 - 9 * x4 >= 0)
model.addConstr(-4 * x2 + 3 * x3 >= 0)
model.addConstr(18 * x1 + 7 * x5 <= 38)
model.addConstr(3 * x2 + 7 * x5 <= 91)
model.addConstr(18 * x1 + 3 * x2 + 17 * x3 <= 34)

# Optimize the model
model.optimize()

# Print the solution
if model.status == gurobi.GRB.OPTIMAL:
    print("Objective: ", model.objval)
    print("Ravioli: ", x1.varValue)
    print("Cheeseburgers: ", x2.varValue)
    print("Steaks: ", x3.varValue)
    print("Bagged Salads: ", x4.varValue)
    print("Hamburgers: ", x5.varValue)
else:
    print("The model is infeasible")
```