```json
{
  "sym_variables": [
    ("x0", "grams of fat"),
    ("x1", "milligrams of potassium"),
    ("x2", "milligrams of vitamin C"),
    ("x3", "milligrams of calcium")
  ],
  "objective_function": "3*x0 + 3*x1 + 7*x2 + 1*x3",
  "constraints": [
    "17*x0 + 2*x3 >= 55",
    "16*x1 + 2*x3 >= 62",
    "19*x0 + 18*x3 >= 48",
    "19*x2 + 18*x3 >= 37",
    "19*x0 + 16*x1 + 18*x3 >= 41",
    "19*x0 + 16*x1 + 19*x2 >= 41",
    "9*x0 + 3*x2 >= 57",
    "9*x0 + 16*x1 >= 57",
    "16*x1 + 3*x2 >= 68",
    "3*x2 + 17*x3 >= 40",
    "6*x0 + 8*x2 - 4*x3 >= 0",
    "15*x2 + 2*x3 <= 360",
    "17*x0 + 16*x1 <= 446",
    "17*x0 + 2*x3 <= 335",
    "17*x0 + 15*x2 + 2*x3 <= 316",
    "17*x0 + 16*x1 + 15*x2 + 2*x3 <= 316",
    "19*x2 + 18*x3 <= 140",
    "19*x0 + 16*x1 <= 118",
    "16*x1 + 19*x2 <= 86",
    "19*x0 + 16*x1 + 19*x2 + 18*x3 <= 86",
    "16*x0 + 8*x2 <= 405",
    "7*x1 + 6*x3 <= 289",
    "7*x1 + 8*x2 <= 448",
    "16*x0 + 7*x1 <= 427",
    "16*x0 + 6*x3 <= 481",
    "16*x0 + 7*x1 + 8*x2 + 6*x3 <= 481",
    "9*x0 + 17*x3 <= 283",
    "16*x1 + 3*x2 <= 332",
    "9*x0 + 16*x1 <= 173",
    "16*x1 + 17*x3 <= 383",
    "16*x1 + 3*x2 + 17*x3 <= 361",
    "9*x0 + 16*x1 + 3*x2 + 17*x3 <= 361",
    "x0 >= 0",
    "x1 >= 0",
    "x2 >= 0",
    "x3 >= 0"
  ]
}
```

```python
import gurobipy as gp

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

    # Create variables
    x0 = m.addVar(vtype=gp.GRB.CONTINUOUS, name="x0")  # grams of fat
    x1 = m.addVar(vtype=gp.GRB.CONTINUOUS, name="x1")  # milligrams of potassium
    x2 = m.addVar(vtype=gp.GRB.CONTINUOUS, name="x2")  # milligrams of vitamin C
    x3 = m.addVar(vtype=gp.GRB.CONTINUOUS, name="x3")  # milligrams of calcium


    # Set objective function
    m.setObjective(3*x0 + 3*x1 + 7*x2 + 1*x3, gp.GRB.MAXIMIZE)

    # Add constraints
    m.addConstr(17*x0 + 2*x3 >= 55)
    m.addConstr(16*x1 + 2*x3 >= 62)
    m.addConstr(19*x0 + 18*x3 >= 48)
    m.addConstr(19*x2 + 18*x3 >= 37)
    m.addConstr(19*x0 + 16*x1 + 18*x3 >= 41)
    m.addConstr(19*x0 + 16*x1 + 19*x2 >= 41)
    m.addConstr(9*x0 + 3*x2 >= 57)
    m.addConstr(9*x0 + 16*x1 >= 57)
    m.addConstr(16*x1 + 3*x2 >= 68)
    m.addConstr(3*x2 + 17*x3 >= 40)
    m.addConstr(6*x0 + 8*x2 - 4*x3 >= 0)
    m.addConstr(15*x2 + 2*x3 <= 360)
    m.addConstr(17*x0 + 16*x1 <= 446)
    m.addConstr(17*x0 + 2*x3 <= 335)
    m.addConstr(17*x0 + 15*x2 + 2*x3 <= 316)
    m.addConstr(17*x0 + 16*x1 + 15*x2 + 2*x3 <= 316)
    m.addConstr(19*x2 + 18*x3 <= 140)
    m.addConstr(19*x0 + 16*x1 <= 118)
    m.addConstr(16*x1 + 19*x2 <= 86)
    m.addConstr(19*x0 + 16*x1 + 19*x2 + 18*x3 <= 86)
    m.addConstr(16*x0 + 8*x2 <= 405)
    m.addConstr(7*x1 + 6*x3 <= 289)
    m.addConstr(7*x1 + 8*x2 <= 448)
    m.addConstr(16*x0 + 7*x1 <= 427)
    m.addConstr(16*x0 + 6*x3 <= 481)
    m.addConstr(16*x0 + 7*x1 + 8*x2 + 6*x3 <= 481)
    m.addConstr(9*x0 + 17*x3 <= 283)
    m.addConstr(16*x1 + 3*x2 <= 332)
    m.addConstr(9*x0 + 16*x1 <= 173)
    m.addConstr(16*x1 + 17*x3 <= 383)
    m.addConstr(16*x1 + 3*x2 + 17*x3 <= 361)
    m.addConstr(9*x0 + 16*x1 + 3*x2 + 17*x3 <= 361)


    # Optimize model
    m.optimize()

    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('Optimization problem is infeasible.')
    else:
        print('Optimization ended with status %d' % m.status)


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

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