## Step 1: Define the symbolic representation of the variables
The variables are defined as follows: 
- $x_0$ represents 'coleus'
- $x_1$ represents 'carrots'
- $x_2$ represents 'tulips'
- $x_3$ represents 'decorative cabbages'

## Step 2: Convert the objective function into symbolic notation
The objective function to minimize is $4.71x_0 + 4.67x_1 + 7.23x_2 + 8.21x_3$.

## Step 3: List all constraints in symbolic notation
Constraints:
1. $12x_0 \leq 287$
2. $18x_0 \leq 402$
3. $11x_1 \leq 287$
4. $6x_1 \leq 402$
5. $2x_2 \leq 287$
6. $10x_2 \leq 402$
7. $20x_3 \leq 287$
8. $5x_3 \leq 402$
9. $12x_0 + 11x_1 \geq 63$
10. $12x_0 + 2x_2 \geq 71$
11. $2x_2 + 20x_3 \geq 49$
12. $11x_1 + 2x_2 \geq 33$
13. $11x_1 + 20x_3 \geq 39$
14. $12x_0 + 11x_1 + 2x_2 \geq 58$
15. $12x_0 + 2x_2 + 20x_3 \geq 58$
16. $11x_1 + 2x_2 + 20x_3 \geq 58$
17. $12x_0 + 11x_1 + 2x_2 \geq 65$
18. $12x_0 + 2x_2 + 20x_3 \geq 65$
19. $11x_1 + 2x_2 + 20x_3 \geq 65$
20. $12x_0 + 11x_1 + 2x_2 \geq 42$
21. $12x_0 + 2x_2 + 20x_3 \geq 42$
22. $11x_1 + 2x_2 + 20x_3 \geq 42$
23. $12x_0 + 11x_1 + 2x_2 + 20x_3 \geq 42$
24. $10x_2 + 5x_3 \geq 97$
25. $6x_1 + 5x_3 \geq 86$
26. $18x_0 + 6x_1 \geq 86$
27. $18x_0 + 6x_1 + 10x_2 + 5x_3 \geq 86$
28. $6x_1 - 3x_2 \geq 0$
29. $11x_1 + 2x_2 \leq 110$
30. $2x_2 + 20x_3 \leq 215$
31. $12x_0 + 11x_1 \leq 129$
32. $10x_2 + 5x_3 \leq 121$
33. $6x_1 + 10x_2 \leq 364$
34. $18x_0 + 6x_1 + 5x_3 \leq 231$
35. $18x_0 + 10x_2 + 5x_3 \leq 249$
36. $18x_0 + 6x_1 + 10x_2 \leq 173$
37. $6x_1 + 10x_2 + 5x_3 \leq 191$

## Step 4: Define the symbolic representation of the problem
```json
{
    'sym_variables': [
        ('x0', 'coleus'), 
        ('x1', 'carrots'), 
        ('x2', 'tulips'), 
        ('x3', 'decorative cabbages')
    ], 
    'objective_function': '4.71*x0 + 4.67*x1 + 7.23*x2 + 8.21*x3', 
    'constraints': [
        '12*x0 <= 287',
        '18*x0 <= 402',
        '11*x1 <= 287',
        '6*x1 <= 402',
        '2*x2 <= 287',
        '10*x2 <= 402',
        '20*x3 <= 287',
        '5*x3 <= 402',
        '12*x0 + 11*x1 >= 63',
        '12*x0 + 2*x2 >= 71',
        '2*x2 + 20*x3 >= 49',
        '11*x1 + 2*x2 >= 33',
        '11*x1 + 20*x3 >= 39',
        '12*x0 + 11*x1 + 2*x2 >= 58',
        '12*x0 + 2*x2 + 20*x3 >= 58',
        '11*x1 + 2*x2 + 20*x3 >= 58',
        '12*x0 + 11*x1 + 2*x2 >= 65',
        '12*x0 + 2*x2 + 20*x3 >= 65',
        '11*x1 + 2*x2 + 20*x3 >= 65',
        '12*x0 + 11*x1 + 2*x2 >= 42',
        '12*x0 + 2*x2 + 20*x3 >= 42',
        '11*x1 + 2*x2 + 20*x3 >= 42',
        '12*x0 + 11*x1 + 2*x2 + 20*x3 >= 42',
        '10*x2 + 5*x3 >= 97',
        '6*x1 + 5*x3 >= 86',
        '18*x0 + 6*x1 >= 86',
        '18*x0 + 6*x1 + 10*x2 + 5*x3 >= 86',
        '6*x1 - 3*x2 >= 0',
        '11*x1 + 2*x2 <= 110',
        '2*x2 + 20*x3 <= 215',
        '12*x0 + 11*x1 <= 129',
        '10*x2 + 5*x3 <= 121',
        '6*x1 + 10*x2 <= 364',
        '18*x0 + 6*x1 + 5*x3 <= 231',
        '18*x0 + 10*x2 + 5*x3 <= 249',
        '18*x0 + 6*x1 + 10*x2 <= 173',
        '6*x1 + 10*x2 + 5*x3 <= 191'
    ]
}
```

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

def solve_optimization_problem():
    # Create a new Gurobi model
    model = gurobi.Model()

    # Define the variables
    x0 = model.addVar(name='coleus', vtype=gurobi.GRB.INTEGER)
    x1 = model.addVar(name='carrots', vtype=gurobi.GRB.INTEGER)
    x2 = model.addVar(name='tulips', vtype=gurobi.GRB.INTEGER)
    x3 = model.addVar(name='decorative_cabbages', vtype=gurobi.GRB.INTEGER)

    # Define the objective function
    model.setObjective(4.71 * x0 + 4.67 * x1 + 7.23 * x2 + 8.21 * x3, gurobi.GRB.MINIMIZE)

    # Add constraints
    model.addConstr(12 * x0 <= 287)
    model.addConstr(18 * x0 <= 402)
    model.addConstr(11 * x1 <= 287)
    model.addConstr(6 * x1 <= 402)
    model.addConstr(2 * x2 <= 287)
    model.addConstr(10 * x2 <= 402)
    model.addConstr(20 * x3 <= 287)
    model.addConstr(5 * x3 <= 402)
    model.addConstr(12 * x0 + 11 * x1 >= 63)
    model.addConstr(12 * x0 + 2 * x2 >= 71)
    model.addConstr(2 * x2 + 20 * x3 >= 49)
    model.addConstr(11 * x1 + 2 * x2 >= 33)
    model.addConstr(11 * x1 + 20 * x3 >= 39)
    model.addConstr(12 * x0 + 11 * x1 + 2 * x2 >= 58)
    model.addConstr(12 * x0 + 2 * x2 + 20 * x3 >= 58)
    model.addConstr(11 * x1 + 2 * x2 + 20 * x3 >= 58)
    model.addConstr(12 * x0 + 11 * x1 + 2 * x2 >= 65)
    model.addConstr(12 * x0 + 2 * x2 + 20 * x3 >= 65)
    model.addConstr(11 * x1 + 2 * x2 + 20 * x3 >= 65)
    model.addConstr(12 * x0 + 11 * x1 + 2 * x2 >= 42)
    model.addConstr(12 * x0 + 2 * x2 + 20 * x3 >= 42)
    model.addConstr(11 * x1 + 2 * x2 + 20 * x3 >= 42)
    model.addConstr(12 * x0 + 11 * x1 + 2 * x2 + 20 * x3 >= 42)
    model.addConstr(10 * x2 + 5 * x3 >= 97)
    model.addConstr(6 * x1 + 5 * x3 >= 86)
    model.addConstr(18 * x0 + 6 * x1 >= 86)
    model.addConstr(18 * x0 + 6 * x1 + 10 * x2 + 5 * x3 >= 86)
    model.addConstr(6 * x1 - 3 * x2 >= 0)
    model.addConstr(11 * x1 + 2 * x2 <= 110)
    model.addConstr(2 * x2 + 20 * x3 <= 215)
    model.addConstr(12 * x0 + 11 * x1 <= 129)
    model.addConstr(10 * x2 + 5 * x3 <= 121)
    model.addConstr(6 * x1 + 10 * x2 <= 364)
    model.addConstr(18 * x0 + 6 * x1 + 5 * x3 <= 231)
    model.addConstr(18 * x0 + 10 * x2 + 5 * x3 <= 249)
    model.addConstr(18 * x0 + 6 * x1 + 10 * x2 <= 173)
    model.addConstr(6 * x1 + 10 * x2 + 5 * x3 <= 191)

    # Solve the model
    model.optimize()

    # Print the solution
    if model.status == gurobi.GRB.OPTIMAL:
        print('Objective: ', model.objVal)
        print('Coleus: ', x0.varValue)
        print('Carrots: ', x1.varValue)
        print('Tulips: ', x2.varValue)
        print('Decorative Cabbages: ', x3.varValue)
    else:
        print('No optimal solution found')

solve_optimization_problem()
```