To solve the given optimization problem, we first need to convert the natural language description into a symbolic representation. This involves defining variables and formulating the objective function and constraints in terms of these variables.

Let's define:
- $x_1$ as the number of orders of burritos sold,
- $x_2$ as the number of orders of tacitos sold.

The objective is to maximize revenue, which can be represented by the objective function: $17x_1 + 12x_2$.

The constraints based on the problem description are:
1. The food truck must sell at least 30 orders of burritos: $x_1 \geq 30$.
2. The food truck can make at most 100 orders of burritos: $x_1 \leq 100$.
3. The food truck must sell at least 20 orders of tacitos: $x_2 \geq 20$.
4. The food truck can make at most 150 orders of tacitos: $x_2 \leq 150$.
5. The total number of orders cannot exceed 250: $x_1 + x_2 \leq 250$.

All variables are non-negative since they represent quantities of items sold: $x_1, x_2 \geq 0$.

In symbolic representation:
```json
{
  'sym_variables': [('x1', 'number of orders of burritos'), ('x2', 'number of orders of tacitos')],
  'objective_function': '17*x1 + 12*x2',
  'constraints': ['x1 >= 30', 'x1 <= 100', 'x2 >= 20', 'x2 <= 150', 'x1 + x2 <= 250']
}
```

To solve this problem using Gurobi in Python, we can use the following code:

```python
from gurobipy import *

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

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

# Set objective function
m.setObjective(17*x1 + 12*x2, GRB.MAXIMIZE)

# Add constraints
m.addConstr(x1 >= 30, name="min_burritos")
m.addConstr(x1 <= 100, name="max_burritos")
m.addConstr(x2 >= 20, name="min_tacitos")
m.addConstr(x2 <= 150, name="max_tacitos")
m.addConstr(x1 + x2 <= 250, name="total_orders")

# Optimize model
m.optimize()

# Print solution
if m.status == GRB.OPTIMAL:
    print("Optimal solution found:")
    print(f"Burritos: {x1.x}")
    print(f"Tacitos: {x2.x}")
    print(f"Revenue: {17*x1.x + 12*x2.x}")
else:
    print("No optimal solution found")
```