```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 + 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",
    "12 * x0 <= 287",
    "18 * x0 <= 402",
    "x0, x1, x2, x3 are integers"


  ]
}
```

```python
import gurobipy as gp

# Create a new model
m = gp.Model("optimization_problem")

# Create variables
coleus = m.addVar(vtype=gp.GRB.INTEGER, name="coleus")
carrots = m.addVar(vtype=gp.GRB.INTEGER, name="carrots")
tulips = m.addVar(vtype=gp.GRB.INTEGER, name="tulips")
decorative_cabbages = m.addVar(vtype=gp.GRB.INTEGER, name="decorative_cabbages")


# Set objective function
m.setObjective(4.71 * coleus + 4.67 * carrots + 7.23 * tulips + 8.21 * decorative_cabbages, gp.GRB.MINIMIZE)

# Add constraints
m.addConstr(12 * coleus + 11 * carrots >= 63)
m.addConstr(12 * coleus + 2 * tulips >= 71)
m.addConstr(2 * tulips + 20 * decorative_cabbages >= 49)
m.addConstr(11 * carrots + 2 * tulips >= 33)
m.addConstr(11 * carrots + 20 * decorative_cabbages >= 39)
m.addConstr(12 * coleus + 11 * carrots + 2 * tulips >= 58)
m.addConstr(12 * coleus + 2 * tulips + 20 * decorative_cabbages >= 58)
m.addConstr(11 * carrots + 2 * tulips + 20 * decorative_cabbages >= 58)
m.addConstr(12 * coleus + 11 * carrots + 2 * tulips >= 65)
m.addConstr(12 * coleus + 2 * tulips + 20 * decorative_cabbages >= 65)
m.addConstr(11 * carrots + 2 * tulips + 20 * decorative_cabbages >= 65)
m.addConstr(12 * coleus + 11 * carrots + 2 * tulips >= 42)
m.addConstr(12 * coleus + 2 * tulips + 20 * decorative_cabbages >= 42)
m.addConstr(11 * carrots + 2 * tulips + 20 * decorative_cabbages >= 42)
m.addConstr(12 * coleus + 11 * carrots + 2 * tulips + 20 * decorative_cabbages >= 42)
m.addConstr(10 * tulips + 5 * decorative_cabbages >= 97)
m.addConstr(6 * carrots + 5 * decorative_cabbages >= 86)
m.addConstr(18 * coleus + 6 * carrots >= 86)
m.addConstr(18 * coleus + 6 * carrots + 10 * tulips + 5 * decorative_cabbages >= 86)
m.addConstr(6 * carrots - 3 * tulips >= 0)
m.addConstr(11 * carrots + 2 * tulips <= 110)
m.addConstr(2 * tulips + 20 * decorative_cabbages <= 215)
m.addConstr(12 * coleus + 11 * carrots <= 129)
m.addConstr(10 * tulips + 5 * decorative_cabbages <= 121)
m.addConstr(6 * carrots + 10 * tulips <= 364)
m.addConstr(18 * coleus + 6 * carrots + 5 * decorative_cabbages <= 231)
m.addConstr(18 * coleus + 10 * tulips + 5 * decorative_cabbages <= 249)
m.addConstr(18 * coleus + 6 * carrots + 10 * tulips <= 173)
m.addConstr(6 * carrots + 10 * tulips + 5 * decorative_cabbages <= 191)

m.addConstr(12 * coleus <= 287)
m.addConstr(18 * coleus <= 402)



# Optimize model
m.optimize()

# Print solution
if m.status == gp.GRB.OPTIMAL:
    print('Obj: %g' % m.objVal)
    for v in m.getVars():
        print('%s %g' % (v.varName, v.x))
elif m.status == gp.GRB.INFEASIBLE:
    print('The problem is infeasible.')
```