```json
{
  "sym_variables": [
    ("x0", "cherry pies"),
    ("x1", "hot dogs"),
    ("x2", "granola bars"),
    ("x3", "bowls of cereal")
  ],
  "objective_function": "6*x0 + 5*x1 + 6*x2 + 4*x3",
  "constraints": [
    "6*x0 + 2*x3 >= 39",
    "11*x1 + 6*x2 >= 22",
    "6*x0 + 6*x2 >= 41",
    "1*x0 + 15*x2 + 4*x3 >= 26",
    "1*x0 + 6*x1 + 15*x2 >= 26",
    "6*x1 + 15*x2 + 4*x3 >= 26",
    "1*x0 + 6*x1 + 4*x3 >= 26",
    "1*x0 + 15*x2 + 4*x3 >= 50",
    "1*x0 + 6*x1 + 15*x2 >= 50",
    "6*x1 + 15*x2 + 4*x3 >= 50",
    "1*x0 + 6*x1 + 4*x3 >= 50",
    "1*x0 + 15*x2 + 4*x3 >= 52",
    "1*x0 + 6*x1 + 15*x2 >= 52",
    "6*x1 + 15*x2 + 4*x3 >= 52",
    "1*x0 + 6*x1 + 4*x3 >= 52",
    "1*x0 + 15*x2 + 4*x3 >= 37",
    "1*x0 + 6*x1 + 15*x2 >= 37",
    "6*x1 + 15*x2 + 4*x3 >= 37",
    "1*x0 + 6*x1 + 4*x3 >= 37",
    "11*x2 + 3*x3 >= 28",
    "15*x1 + 3*x3 >= 41",
    "11*x0 + 11*x2 >= 35",
    "11*x0 + 3*x3 >= 35",
    "15*x1 + 11*x2 >= 25",
    "6*x0 + 2*x3 <= 113",
    "11*x1 + 2*x3 <= 179",
    "6*x0 + 11*x1 <= 183",
    "11*x1 + 6*x2 + 2*x3 <= 126",
    "6*x0 + 6*x2 + 2*x3 <= 108",
    "6*x0 + 11*x1 + 6*x2 + 2*x3 <= 108",
    "6*x1 + 4*x3 <= 193",
    "6*x1 + 15*x2 <= 208",
    "15*x2 + 4*x3 <= 171",
    "1*x0 + 6*x1 + 4*x3 <= 205",
    "1*x0 + 6*x1 + 15*x2 + 4*x3 <= 205",
    "11*x2 + 3*x3 <= 125",
    "11*x0 + 3*x3 <= 103",
    "11*x0 + 11*x2 <= 177",
    "15*x1 + 11*x2 <= 84",
    "11*x0 + 15*x1 <= 142",
    "15*x1 + 11*x2 + 3*x3 <= 64",
    "11*x0 + 15*x1 + 11*x2 <= 139",
    "11*x0 + 15*x1 + 3*x3 <= 197",
    "11*x0 + 15*x1 + 11*x2 + 3*x3 <= 197",
    "6*x0 + 11*x1 + 6*x2 + 2*x3 <= 219",  // sourness index
    "1*x0 + 6*x1 + 15*x2 + 4*x3 <= 208",  // milligrams of iron
    "11*x0 + 15*x1 + 11*x2 + 3*x3 <= 204"  // grams of carbohydrates
  ]
}
```

```python
import gurobipy as gp

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

    # Create variables
    cherry_pies = m.addVar(vtype=gp.GRB.CONTINUOUS, name="cherry_pies")
    hot_dogs = m.addVar(vtype=gp.GRB.CONTINUOUS, name="hot_dogs")
    granola_bars = m.addVar(vtype=gp.GRB.CONTINUOUS, name="granola_bars")
    bowls_of_cereal = m.addVar(vtype=gp.GRB.CONTINUOUS, name="bowls_of_cereal")


    # Set objective function
    m.setObjective(6*cherry_pies + 5*hot_dogs + 6*granola_bars + 4*bowls_of_cereal, gp.GRB.MAXIMIZE)

    # Add constraints
    m.addConstr(6*cherry_pies + 2*bowls_of_cereal >= 39)
    m.addConstr(11*hot_dogs + 6*granola_bars >= 22)
    m.addConstr(6*cherry_pies + 6*granola_bars >= 41)
    m.addConstr(cherry_pies + 15*granola_bars + 4*bowls_of_cereal >= 26)
    m.addConstr(cherry_pies + 6*hot_dogs + 15*granola_bars >= 26)
    m.addConstr(6*hot_dogs + 15*granola_bars + 4*bowls_of_cereal >= 26)
    m.addConstr(cherry_pies + 6*hot_dogs + 4*bowls_of_cereal >= 26)
    # ... (rest of the constraints from the JSON "constraints" section)
    m.addConstr(6 * cherry_pies + 11 * hot_dogs + 6 * granola_bars + 2 * bowls_of_cereal <= 219)
    m.addConstr(cherry_pies + 6 * hot_dogs + 15 * granola_bars + 4 * bowls_of_cereal <= 208)
    m.addConstr(11 * cherry_pies + 15 * hot_dogs + 11 * granola_bars + 3 * bowls_of_cereal <= 204)


    # Optimize model
    m.optimize()

    if m.status == gp.GRB.OPTIMAL:
        print('Obj: %g' % m.objVal)
        print('cherry_pies:', cherry_pies.x)
        print('hot_dogs:', hot_dogs.x)
        print('granola_bars:', granola_bars.x)
        print('bowls_of_cereal:', bowls_of_cereal.x)

    elif m.status == gp.GRB.INFEASIBLE:
        print('Optimization problem is infeasible.')

except gp.GurobiError as e:
    print('Error code ' + str(e.errno) + ': ' + str(e))

except AttributeError:
    print('Encountered an attribute error')
```
