## Step 1: Define the symbolic representation of the problem
The problem involves minimizing an objective function subject to various constraints. The variables are:
- $x_0$: lightbulbs
- $x_1$: packs of napkins
- $x_2$: rubber gloves
- $x_3$: diapers
- $x_4$: dish soap bottles

## Step 2: Formulate the objective function
The objective function to minimize is: $6.05x_0 + 1.69x_1 + 9.85x_2 + 2.96x_3 + 2.44x_4$

## Step 3: List the constraints
Constraints include:
- Sustainability score constraints:
  - $x_0 + 19x_2 \geq 83$
  - $10x_3 + 11x_4 \geq 67$
  - $x_0 + 26x_1 + 19x_2 \geq 101$
  - $x_0 + 26x_1 + 11x_4 \geq 101$
  - $x_0 + 26x_1 + 19x_2 \geq 76$
  - $x_0 + 26x_1 + 11x_4 \geq 76$
  - $x_0 + 26x_1 + 19x_2 + 10x_3 + 11x_4 \geq 76$
- Value constraints:
  - $6x_3 + 22x_4 \geq 65$
  - $20x_1 + 6x_3 \geq 76$
  - $26x_0 + 22x_4 \geq 76$
  - $20x_1 + 22x_4 \geq 85$
  - $20x_1 + 15x_2 \geq 49$
  - $26x_0 + 20x_1 \geq 42$
  - $26x_0 + 6x_3 + 22x_4 \geq 65$
  - $15x_2 + 6x_3 + 22x_4 \geq 65$
  - $20x_1 + 15x_2 + 22x_4 \geq 65$
  - $26x_0 + 15x_2 + 22x_4 \geq 65$
  - ... (many more value constraints)
- Storage space constraints:
  - $17x_0 + 10x_2 + 8x_3 \geq 39$
  - $17x_0 + 8x_4 \geq 26$
  - $2x_1 + 10x_2 + 8x_3 \geq 39$
  - ... (many more storage space constraints)
- Weight constraints:
  - $9x_1 + 26x_4 \geq 41$
  - $15x_3 + 26x_4 \geq 34$
  - ... (many more weight constraints)
- Other constraints:
  - $-8x_1 + 7x_2 \geq 0$
  - $-3x_1 + 2x_3 \geq 0$
  - $x_0 + 19x_2 \leq 532$
  - ... (many more constraints)

## 4: Convert the problem into Gurobi code
```python
import gurobi

# Define the model
m = gurobi.Model()

# Define the variables
x0 = m.addVar(name="lightbulbs", vtype=gurobi.GRB.INTEGER)
x1 = m.addVar(name="packs of napkins", vtype=gurobi.GRB.INTEGER)
x2 = m.addVar(name="rubber gloves", vtype=gurobi.GRB.INTEGER)
x3 = m.addVar(name="diapers", vtype=gurobi.GRB.INTEGER)
x4 = m.addVar(name="dish soap bottles", vtype=gurobi.GRB.INTEGER)

# Define the objective function
m.setObjective(6.05 * x0 + 1.69 * x1 + 9.85 * x2 + 2.96 * x3 + 2.44 * x4, gurobi.GRB.MINIMIZE)

# Add constraints
# Sustainability score constraints
m.addConstr(x0 + 19 * x2 >= 83)
m.addConstr(10 * x3 + 11 * x4 >= 67)
m.addConstr(x0 + 26 * x1 + 19 * x2 >= 101)
m.addConstr(x0 + 26 * x1 + 11 * x4 >= 101)
m.addConstr(x0 + 26 * x1 + 19 * x2 >= 76)
m.addConstr(x0 + 26 * x1 + 11 * x4 >= 76)
m.addConstr(x0 + 26 * x1 + 19 * x2 + 10 * x3 + 11 * x4 >= 76)

# Value constraints
m.addConstr(6 * x3 + 22 * x4 >= 65)
m.addConstr(20 * x1 + 6 * x3 >= 76)
m.addConstr(26 * x0 + 22 * x4 >= 76)
m.addConstr(20 * x1 + 22 * x4 >= 85)
m.addConstr(20 * x1 + 15 * x2 >= 49)
m.addConstr(26 * x0 + 20 * x1 >= 42)
m.addConstr(26 * x0 + 6 * x3 + 22 * x4 >= 65)
m.addConstr(15 * x2 + 6 * x3 + 22 * x4 >= 65)
m.addConstr(20 * x1 + 15 * x2 + 22 * x4 >= 65)
m.addConstr(26 * x0 + 15 * x2 + 22 * x4 >= 65)

# Storage space constraints
m.addConstr(17 * x0 + 10 * x2 + 8 * x3 >= 39)
m.addConstr(17 * x0 + 8 * x4 >= 26)
m.addConstr(2 * x1 + 10 * x2 + 8 * x3 >= 39)

# Weight constraints
m.addConstr(9 * x1 + 26 * x4 >= 41)
m.addConstr(15 * x3 + 26 * x4 >= 34)

# Other constraints
m.addConstr(-8 * x1 + 7 * x2 >= 0)
m.addConstr(-3 * x1 + 2 * x3 >= 0)
m.addConstr(x0 + 19 * x2 <= 532)

# Solve the model
m.optimize()

# Print the solution
if m.status == gurobi.GRB.OPTIMAL:
    print("Objective: ", m.objVal)
    print("Lightbulbs: ", x0.varValue)
    print("Packs of napkins: ", x1.varValue)
    print("Rubber gloves: ", x2.varValue)
    print("Diapers: ", x3.varValue)
    print("Dish soap bottles: ", x4.varValue)
else:
    print("No solution found")
```

## Step 5: Symbolic representation
```json
{
    'sym_variables': [
        ('x0', 'lightbulbs'),
        ('x1', 'packs of napkins'),
        ('x2', 'rubber gloves'),
        ('x3', 'diapers'),
        ('x4', 'dish soap bottles')
    ],
    'objective_function': '6.05x0 + 1.69x1 + 9.85x2 + 2.96x3 + 2.44x4',
    'constraints': [
        'x0 + 19x2 >= 83',
        '10x3 + 11x4 >= 67',
        'x0 + 26x1 + 19x2 >= 101',
        'x0 + 26x1 + 11x4 >= 101',
        'x0 + 26x1 + 19x2 >= 76',
        'x0 + 26x1 + 11x4 >= 76',
        'x0 + 26x1 + 19x2 + 10x3 + 11x4 >= 76',
        '6x3 + 22x4 >= 65',
        '20x1 + 6x3 >= 76',
        '26x0 + 22x4 >= 76',
        '20x1 + 22x4 >= 85',
        '20x1 + 15x2 >= 49',
        '26x0 + 20x1 >= 42',
        '26x0 + 6x3 + 22x4 >= 65',
        '15x2 + 6x3 + 22x4 >= 65',
        '20x1 + 15x2 + 22x4 >= 65',
        '26x0 + 15x2 + 22x4 >= 65',
        '17x0 + 10x2 + 8x3 >= 39',
        '17x0 + 8x4 >= 26',
        '2x1 + 10x2 + 8x3 >= 39',
        '9x1 + 26x4 >= 41',
        '15x3 + 26x4 >= 34',
        '-8x1 + 7x2 >= 0',
        '-3x1 + 2x3 >= 0',
        'x0 + 19x2 <= 532'
    ]
}
```