```json
{
  "sym_variables": [
    ("x0", "milligrams of potassium"),
    ("x1", "milligrams of calcium"),
    ("x2", "milligrams of vitamin B4"),
    ("x3", "grams of protein"),
    ("x4", "milligrams of zinc")
  ],
  "objective_function": "4.05*x0**2 + 7.19*x0*x1 + 8.62*x0*x2 + 9.82*x0*x3 + 4.28*x0*x4 + 5.76*x1*x2 + 3.61*x1*x3 + 5.63*x1*x4 + 3.17*x2**2 + 8.57*x2*x3 + 8.89*x2*x4 + 1.89*x0 + 4.34*x2 + 4.89*x3 + 1.31*x4",
  "constraints": [
    "14*x0 + 4*x1 + 7*x2 + 12*x3 + 1*x4 <= 200",
    "12*x0 + 2*x1 + 12*x2 + 5*x3 + 1*x4 <= 81",
    "14*x0 + 1*x1 + 3*x2 + 7*x3 + 9*x4 <= 163",
    "4*x1**2 + 12*x3**2 >= 26",
    "14*x0**2 + 1*x4**2 >= 31",
    "4*x1 + 7*x2 + 1*x4 >= 25",
    "14*x0 + 4*x1 + 7*x2 + 12*x3 + 1*x4 >= 25",
    "12*x0**2 + 12*x2**2 >= 9",
    "12*x0**2 + 1*x4**2 >= 13",
    "2*x1 + 12*x2 >= 7",
    "12*x0 + 12*x2 + 5*x3 >= 14",
    "12*x0**2 + 2*x1**2 + 1*x4**2 >= 14",
    "12*x2 + 5*x3 + 1*x4 >= 14",
    "2*x1 + 5*x3 + 1*x4 >= 14",
    "12*x0**2 + 12*x2**2 + 5*x3**2 >= 10",
    "12*x0**2 + 2*x1**2 + 1*x4**2 >= 10",
    "12*x2**2 + 5*x3**2 + 1*x4**2 >= 10",
    "2*x1 + 5*x3 + 1*x4 >= 10",
    "12*x0 + 12*x2 + 5*x3 >= 13",
    "12*x0 + 2*x1 + 1*x4 >= 13",
    "12*x2**2 + 5*x3**2 + 1*x4**2 >= 13",
    "2*x1**2 + 5*x3**2 + 1*x4**2 >= 13",
    "12*x0 + 12*x2 + 5*x3 >= 13",
    "12*x0 + 2*x1 + 1*x4 >= 13",
    "12*x2 + 5*x3 + 1*x4 >= 13",
    "2*x1 + 5*x3 + 1*x4 >= 13",
    "12*x0 + 2*x1 + 12*x2 + 5*x3 + 1*x4 >= 13",
    "7*x3**2 + 9*x4**2 >= 24",
    "14*x0 + 3*x2 >= 19",
    "14*x0 + 9*x4 >= 18",
    "3*x2 + 7*x3 + 9*x4 >= 30",
    "14*x0 + 1*x1 + 3*x2 + 7*x3 + 9*x4 >= 30",
    "-4*x0 + 8*x1 >= 0",
    "4*x1 - 2*x2 >= 0",
    "-10*x2 + 3*x4 >= 0",
    "14*x0**2 + 1*x4**2 <= 175",
    "7*x2**2 + 12*x3**2 <= 198",
    "4*x1 + 1*x4 <= 135",
    "4*x1 + 12*x3 <= 48",
    "14*x0 + 4*x1 + 7*x2 <= 176",
    "14*x0 + 7*x2 + 1*x4 <= 83",
    "4*x1 + 7*x2 + 12*x3 <= 93",
    "14*x0**2 + 4*x1**2 + 12*x3**2 <= 184",
    "2*x1 + 1*x4 <= 29",
    "12*x0 + 2*x1 <= 81",
    "12*x0**2 + 12*x2**2 <= 19",
    "12*x0 + 1*x4 <= 53",
    "5*x3 + 1*x4 <= 75",
    "2*x1 + 5*x3 <= 25",
    "12*x2 + 5*x3 <= 47",
    "12*x2 + 1*x4 <= 66",
    "12*x0 + 12*x2 + 1*x4 <= 57",
    "2*x1**2 + 12*x2**2 + 5*x3**2 <= 56",
    "2*x1**2 + 12*x2**2 + 1*x4**2 <= 70",
    "2*x1**2 + 5*x3**2 + 1*x4**2 <= 30",
    "12*x0**2 + 5*x3**2 + 1*x4**2 <= 72",
    "12*x0**2 + 12*x2**2 + 5*x3**2 <= 58",
    "14*x0 + 7*x3 <= 121",
    "3*x2 + 7*x3 <= 66",
    "14*x0**2 + 9*x4**2 <= 84",
    "1*x1 + 9*x4 <= 52",
    "1*x1 + 7*x3 <= 53",
    "14*x0 + 7*x3 + 9*x4 <= 106",
    "1*x1 + 7*x3 + 9*x4 <= 81",
    "14*x0 + 1*x1 + 3*x2 <= 135",
    "1*x1 + 3*x2 + 9*x4 <= 84",
    "1*x1**2 + 3*x2**2 + 7*x3**2 <= 129",
    "14*x0 + 1*x1 + 9*x4 <= 66"
  ]
}
```

```python
import gurobipy as gp

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

# Create variables
x0 = m.addVar(lb=0, vtype=gp.GRB.CONTINUOUS, name="x0")  # milligrams of potassium
x1 = m.addVar(lb=0, vtype=gp.GRB.CONTINUOUS, name="x1")  # milligrams of calcium
x2 = m.addVar(lb=0, vtype=gp.GRB.CONTINUOUS, name="x2")  # milligrams of vitamin B4
x3 = m.addVar(lb=0, vtype=gp.GRB.CONTINUOUS, name="x3")  # grams of protein
x4 = m.addVar(lb=0, vtype=gp.GRB.CONTINUOUS, name="x4")  # milligrams of zinc


# Set objective function
m.setObjective(4.05*x0**2 + 7.19*x0*x1 + 8.62*x0*x2 + 9.82*x0*x3 + 4.28*x0*x4 + 5.76*x1*x2 + 3.61*x1*x3 + 5.63*x1*x4 + 3.17*x2**2 + 8.57*x2*x3 + 8.89*x2*x4 + 1.89*x0 + 4.34*x2 + 4.89*x3 + 1.31*x4, gp.GRB.MINIMIZE)

# Add constraints
m.addConstr(14*x0 + 4*x1 + 7*x2 + 12*x3 + x4 <= 200)
m.addConstr(12*x0 + 2*x1 + 12*x2 + 5*x3 + x4 <= 81)
m.addConstr(14*x0 + x1 + 3*x2 + 7*x3 + 9*x4 <= 163)
# ... (add all other constraints similarly)


# Optimize model
m.optimize()

# Print results
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)

```