## Step 1: Define the symbolic representation of the variables
The variables are ['packs of paper', 'yellow highlighters', 'hole punches', 'black pens'] which can be represented symbolically as $x_0, x_1, x_2, x_3$ respectively.

## Step 2: Convert the objective function into symbolic notation
The objective function to maximize is $6.04 \times \text{packs of paper} + 7.53 \times \text{yellow highlighters} + 4.52 \times \text{hole punches} + 6.92 \times \text{black pens}$, which in symbolic notation is $6.04x_0 + 7.53x_1 + 4.52x_2 + 6.92x_3$.

## 3: List the constraints in symbolic notation
1. $\text{packs of paper} = 25$ or $x_0 = 25$
2. $12 \times \text{packs of paper} + 12 \times \text{yellow highlighters} + 2 \times \text{hole punches} + 24 \times \text{black pens} \geq 103$ or $12x_0 + 12x_1 + 2x_2 + 24x_3 \geq 103$
3. $12x_0 + 12x_1 + 24x_3 \geq 103$
4. $12x_0 + 12x_1 + 2x_2 \geq 103$
5. $12x_0 + 2x_2 + 24x_3 \geq 103$
6. $12x_1 + 2x_2 + 24x_3 \geq 75$
7. $12x_0 + 12x_1 + 24x_3 \geq 75$
8. $12x_0 + 12x_1 + 2x_2 \geq 75$
9. $12x_0 + 2x_2 + 24x_3 \geq 75$
10. $12x_1 + 2x_2 + 24x_3 \geq 102$
11. $12x_0 + 12x_1 + 24x_3 \geq 102$
12. $12x_0 + 12x_1 + 2x_2 \geq 102$
13. $12x_0 + 2x_2 + 24x_3 \geq 102$
14. $12x_1 + 2x_2 + 24x_3 \geq 91$
15. $12x_0 + 12x_1 + 24x_3 \geq 91$
16. $12x_0 + 12x_1 + 2x_2 \geq 91$
17. $12x_0 + 2x_2 + 24x_3 \geq 91$
18. $25x_0 + 12x_2 \leq 203$
19. $25x_0 + 29x_3 \leq 229$
20. $x_1 + 12x_2 \leq 527$
21. $25x_0 + x_1 \leq 552$
22. $x_1 + 29x_3 \leq 374$
23. $25x_0 + 12x_2 + 29x_3 \leq 465$
24. $x_1 + 12x_2 + 29x_3 \leq 193$
25. $25x_0 + x_1 + 12x_2 + 29x_3 \leq 193$
26. $2x_2 + 24x_3 \leq 495$
27. $12x_1 + 2x_2 \leq 509$
28. $12x_0 + 2x_2 \leq 208$
29. $12x_1 + 2x_2 + 24x_3 \leq 179$
30. $12x_0 + 12x_1 + 2x_2 + 24x_3 \leq 179$

## 4: Define the symbolic representation of the problem
```json
{
    'sym_variables': [
        ('x0', 'packs of paper'), 
        ('x1', 'yellow highlighters'), 
        ('x2', 'hole punches'), 
        ('x3', 'black pens')
    ], 
    'objective_function': '6.04x0 + 7.53x1 + 4.52x2 + 6.92x3', 
    'constraints': [
        'x0 = 25',
        '12x0 + 12x1 + 2x2 + 24x3 >= 103',
        '12x0 + 12x1 + 24x3 >= 103',
        '12x0 + 12x1 + 2x2 >= 103',
        '12x0 + 2x2 + 24x3 >= 103',
        '12x1 + 2x2 + 24x3 >= 75',
        '12x0 + 12x1 + 24x3 >= 75',
        '12x0 + 12x1 + 2x2 >= 75',
        '12x0 + 2x2 + 24x3 >= 75',
        '12x1 + 2x2 + 24x3 >= 102',
        '12x0 + 12x1 + 24x3 >= 102',
        '12x0 + 12x1 + 2x2 >= 102',
        '12x0 + 2x2 + 24x3 >= 102',
        '12x1 + 2x2 + 24x3 >= 91',
        '12x0 + 12x1 + 24x3 >= 91',
        '12x0 + 12x1 + 2x2 >= 91',
        '12x0 + 2x2 + 24x3 >= 91',
        '25x0 + 12x2 <= 203',
        '25x0 + 29x3 <= 229',
        'x1 + 12x2 <= 527',
        '25x0 + x1 <= 552',
        'x1 + 29x3 <= 374',
        '25x0 + 12x2 + 29x3 <= 465',
        'x1 + 12x2 + 29x3 <= 193',
        '25x0 + x1 + 12x2 + 29x3 <= 193',
        '2x2 + 24x3 <= 495',
        '12x1 + 2x2 <= 509',
        '12x0 + 2x2 <= 208',
        '12x1 + 2x2 + 24x3 <= 179',
        '12x0 + 12x1 + 2x2 + 24x3 <= 179'
    ]
}
```

## 5: Implement the optimization problem using Gurobi
```python
import gurobi

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

# Define the variables
x0 = m.addVar(vtype=gurobi.GRB.INTEGER, name='x0') # packs of paper
x1 = m.addVar(vtype=gurobi.GRB.INTEGER, name='x1') # yellow highlighters
x2 = m.addVar(vtype=gurobi.GRB.INTEGER, name='x2') # hole punches
x3 = m.addVar(vtype=gurobi.GRB.INTEGER, name='x3') # black pens

# Set the objective function
m.setObjective(6.04 * x0 + 7.53 * x1 + 4.52 * x2 + 6.92 * x3, gurobi.GRB.MAXIMIZE)

# Add constraints
m.addConstr(x0 == 25, name='c1')
m.addConstr(12 * x0 + 12 * x1 + 2 * x2 + 24 * x3 >= 103, name='c2')
m.addConstr(12 * x0 + 12 * x1 + 24 * x3 >= 103, name='c3')
m.addConstr(12 * x0 + 12 * x1 + 2 * x2 >= 103, name='c4')
m.addConstr(12 * x0 + 2 * x2 + 24 * x3 >= 103, name='c5')
m.addConstr(12 * x1 + 2 * x2 + 24 * x3 >= 75, name='c6')
m.addConstr(12 * x0 + 12 * x1 + 24 * x3 >= 75, name='c7')
m.addConstr(12 * x0 + 12 * x1 + 2 * x2 >= 75, name='c8')
m.addConstr(12 * x0 + 2 * x2 + 24 * x3 >= 75, name='c9')
m.addConstr(12 * x1 + 2 * x2 + 24 * x3 >= 102, name='c10')
m.addConstr(12 * x0 + 12 * x1 + 24 * x3 >= 102, name='c11')
m.addConstr(12 * x0 + 12 * x1 + 2 * x2 >= 102, name='c12')
m.addConstr(12 * x0 + 2 * x2 + 24 * x3 >= 102, name='c13')
m.addConstr(12 * x1 + 2 * x2 + 24 * x3 >= 91, name='c14')
m.addConstr(12 * x0 + 12 * x1 + 24 * x3 >= 91, name='c15')
m.addConstr(12 * x0 + 12 * x1 + 2 * x2 >= 91, name='c16')
m.addConstr(12 * x0 + 2 * x2 + 24 * x3 >= 91, name='c17')
m.addConstr(25 * x0 + 12 * x2 <= 203, name='c18')
m.addConstr(25 * x0 + 29 * x3 <= 229, name='c19')
m.addConstr(x1 + 12 * x2 <= 527, name='c20')
m.addConstr(25 * x0 + x1 <= 552, name='c21')
m.addConstr(x1 + 29 * x3 <= 374, name='c22')
m.addConstr(25 * x0 + 12 * x2 + 29 * x3 <= 465, name='c23')
m.addConstr(x1 + 12 * x2 + 29 * x3 <= 193, name='c24')
m.addConstr(25 * x0 + x1 + 12 * x2 + 29 * x3 <= 193, name='c25')
m.addConstr(2 * x2 + 24 * x3 <= 495, name='c26')
m.addConstr(12 * x1 + 2 * x2 <= 509, name='c27')
m.addConstr(12 * x0 + 2 * x2 <= 208, name='c28')
m.addConstr(12 * x1 + 2 * x2 + 24 * x3 <= 179, name='c29')
m.addConstr(12 * x0 + 12 * x1 + 2 * x2 + 24 * x3 <= 179, name='c30')

# Solve the model
m.optimize()

# Print the solution
if m.status == gurobi.GRB.OPTIMAL:
    print('Objective: ', m.objVal)
    print('x0: ', x0.varValue)
    print('x1: ', x1.varValue)
    print('x2: ', x2.varValue)
    print('x3: ', x3.varValue)
else:
    print('The model is infeasible')
```