## Step 1: Define the symbolic representation of the variables
The variables are defined as follows: 
- $x_0$ represents 'milligrams of zinc'
- $x_1$ represents 'milligrams of vitamin B12'
- $x_2$ represents 'milligrams of vitamin B3'
- $x_3$ represents 'milligrams of vitamin C'

## Step 2: Convert the objective function into a symbolic representation
The objective function to minimize is $7.5x_0 + 5.18x_1 + 3.52x_2 + 8.91x_3$.

## Step 3: List all the constraints in symbolic notation
Constraints:
1. $5x_0 \leq 194$
2. $5x_0 \leq 316$
3. $x_1 \leq 194$
4. $2x_1 \leq 316$
5. $18x_2 \leq 194$
6. $13x_2 \leq 316$
7. $19x_3 \leq 194$
8. $5x_3 \leq 316$
9. $5x_0 + x_1 \geq 36$
10. $5x_0 + 18x_2 \geq 19$
11. $x_1 + 18x_2 + 19x_3 \geq 29$
12. $5x_0 + x_1 + 19x_3 \geq 29$
13. $5x_0 + 18x_2 + 19x_3 \geq 29$
14. $x_1 + 18x_2 + 19x_3 \geq 42$
15. $5x_0 + x_1 + 19x_3 \geq 42$
16. $5x_0 + 18x_2 + 19x_3 \geq 42$
17. $x_1 + 18x_2 + 19x_3 \geq 32$
18. $5x_0 + x_1 + 19x_3 \geq 32$
19. $5x_0 + 18x_2 + 19x_3 \geq 32$
20. $5x_0 + x_1 + 18x_2 + 19x_3 \geq 32$
21. $2x_1 + 5x_3 \geq 69$
22. $2x_1 + 13x_2 \geq 61$
23. $5x_0 + 13x_2 \geq 64$
24. $5x_0 + 5x_3 \geq 30$
25. $5x_0 + 13x_2 + 5x_3 \geq 77$
26. $5x_0 + 2x_1 + 13x_2 + 5x_3 \geq 77$
27. $8x_1 - 4x_2 \geq 0$
28. $5x_0 + x_1 + 19x_3 \leq 100$
29. $5x_0 + x_1 + 18x_2 \leq 194$
30. $5x_0 + 18x_2 + 19x_3 \leq 74$
31. $5x_0 + 2x_1 + 13x_2 \leq 279$
32. $5x_0 + 2x_1 + 5x_3 \leq 292$
33. $5x_0 + 13x_2 + 5x_3 \leq 166$

## Step 4: Consider variable bounds and types
- $x_0$ is continuous
- $x_1$ is continuous
- $x_2$ is integer
- $x_3$ is continuous

## 5: Formulate the problem in Gurobi

```python
import gurobi

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

# Define variables
x0 = model.addVar(lb=0, name="milligrams of zinc", vtype=gurobi.GRB.CONTINUOUS)
x1 = model.addVar(lb=0, name="milligrams of vitamin B12", vtype=gurobi.GRB.CONTINUOUS)
x2 = model.addVar(lb=0, name="milligrams of vitamin B3", vtype=gurobi.GRB.INTEGER)
x3 = model.addVar(lb=0, name="milligrams of vitamin C", vtype=gurobi.GRB.CONTINUOUS)

# Objective function
model.setObjective(7.5*x0 + 5.18*x1 + 3.52*x2 + 8.91*x3, gurobi.GRB.MINIMIZE)

# Constraints
model.addConstr(5*x0 <= 194)
model.addConstr(5*x0 <= 316)
model.addConstr(x1 <= 194)
model.addConstr(2*x1 <= 316)
model.addConstr(18*x2 <= 194)
model.addConstr(13*x2 <= 316)
model.addConstr(19*x3 <= 194)
model.addConstr(5*x3 <= 316)
model.addConstr(5*x0 + x1 >= 36)
model.addConstr(5*x0 + 18*x2 >= 19)
model.addConstr(x1 + 18*x2 + 19*x3 >= 29)
model.addConstr(5*x0 + x1 + 19*x3 >= 29)
model.addConstr(5*x0 + 18*x2 + 19*x3 >= 29)
model.addConstr(x1 + 18*x2 + 19*x3 >= 42)
model.addConstr(5*x0 + x1 + 19*x3 >= 42)
model.addConstr(5*x0 + 18*x2 + 19*x3 >= 42)
model.addConstr(x1 + 18*x2 + 19*x3 >= 32)
model.addConstr(5*x0 + x1 + 19*x3 >= 32)
model.addConstr(5*x0 + 18*x2 + 19*x3 >= 32)
model.addConstr(5*x0 + x1 + 18*x2 + 19*x3 >= 32)
model.addConstr(2*x1 + 5*x3 >= 69)
model.addConstr(2*x1 + 13*x2 >= 61)
model.addConstr(5*x0 + 13*x2 >= 64)
model.addConstr(5*x0 + 5*x3 >= 30)
model.addConstr(5*x0 + 13*x2 + 5*x3 >= 77)
model.addConstr(5*x0 + 2*x1 + 13*x2 + 5*x3 >= 77)
model.addConstr(8*x1 - 4*x2 >= 0)
model.addConstr(5*x0 + x1 + 19*x3 <= 100)
model.addConstr(5*x0 + x1 + 18*x2 <= 194)
model.addConstr(5*x0 + 18*x2 + 19*x3 <= 74)
model.addConstr(5*x0 + 2*x1 + 13*x2 <= 279)
model.addConstr(5*x0 + 2*x1 + 5*x3 <= 292)
model.addConstr(5*x0 + 13*x2 + 5*x3 <= 166)

# Optimize the model
model.optimize()

# Print the solution
if model.status == gurobi.GRB.OPTIMAL:
    print("Objective: ", model.objval)
    print("milligrams of zinc: ", x0.varValue)
    print("milligrams of vitamin B12: ", x1.varValue)
    print("milligrams of vitamin B3: ", x2.varValue)
    print("milligrams of vitamin C: ", x3.varValue)
else:
    print("The model is infeasible")
```

```json
{
    'sym_variables': [
        ('x0', 'milligrams of zinc'), 
        ('x1', 'milligrams of vitamin B12'), 
        ('x2', 'milligrams of vitamin B3'), 
        ('x3', 'milligrams of vitamin C')
    ], 
    'objective_function': '7.5*x0 + 5.18*x1 + 3.52*x2 + 8.91*x3', 
    'constraints': [
        '5*x0 <= 194',
        '5*x0 <= 316',
        'x1 <= 194',
        '2*x1 <= 316',
        '18*x2 <= 194',
        '13*x2 <= 316',
        '19*x3 <= 194',
        '5*x3 <= 316',
        '5*x0 + x1 >= 36',
        '5*x0 + 18*x2 >= 19',
        'x1 + 18*x2 + 19*x3 >= 29',
        '5*x0 + x1 + 19*x3 >= 29',
        '5*x0 + 18*x2 + 19*x3 >= 29',
        'x1 + 18*x2 + 19*x3 >= 42',
        '5*x0 + x1 + 19*x3 >= 42',
        '5*x0 + 18*x2 + 19*x3 >= 42',
        'x1 + 18*x2 + 19*x3 >= 32',
        '5*x0 + x1 + 19*x3 >= 32',
        '5*x0 + 18*x2 + 19*x3 >= 32',
        '5*x0 + x1 + 18*x2 + 19*x3 >= 32',
        '2*x1 + 5*x3 >= 69',
        '2*x1 + 13*x2 >= 61',
        '5*x0 + 13*x2 >= 64',
        '5*x0 + 5*x3 >= 30',
        '5*x0 + 13*x2 + 5*x3 >= 77',
        '5*x0 + 2*x1 + 13*x2 + 5*x3 >= 77',
        '8*x1 - 4*x2 >= 0',
        '5*x0 + x1 + 19*x3 <= 100',
        '5*x0 + x1 + 18*x2 <= 194',
        '5*x0 + 18*x2 + 19*x3 <= 74',
        '5*x0 + 2*x1 + 13*x2 <= 279',
        '5*x0 + 2*x1 + 5*x3 <= 292',
        '5*x0 + 13*x2 + 5*x3 <= 166'
    ]
}
```