```json
{
  "sym_variables": [
    ("x0", "rotisserie chickens"),
    ("x1", "protein bars"),
    ("x2", "apples"),
    ("x3", "blueberry pies"),
    ("x4", "green beans")
  ],
  "objective_function": "9.34*x0**2 + 6.55*x0*x1 + 6.61*x0*x3 + 7.75*x1**2 + 2.23*x2**2 + 7.72*x1",
  "constraints": [
    "16*x0 + 25*x1 + 15*x2 + 7*x3 + 3*x4 <= 452",
    "24*x0 + 26*x1 + 25*x2 + 7*x3 + 14*x4 <= 308",
    "7*x0 + 23*x1 + 24*x2 + 15*x3 + 13*x4 <= 372",
    "9*x0 + 8*x1 + 11*x2 + 6*x3 + 5*x4 <= 432",
    "9*x0 + 12*x1 + 5*x2 + 4*x3 + 22*x4 <= 231",
    "25*x1**2 + 3*x4**2 >= 35",
    "15*x2 + 7*x3 >= 82",
    "15*x2**2 + 3*x4**2 >= 45",
    "16*x0**2 + 15*x2**2 >= 37",
    "16*x0**2 + 7*x3**2 >= 59",
    "16*x0 + 25*x1 >= 50",
    "25*x1 + 15*x2 >= 59",
    "7*x3**2 + 3*x4**2 >= 50",
    "16*x0 + 25*x1 + 15*x2 >= 82",
    "16*x0 + 25*x1 + 15*x2 + 7*x3 + 3*x4 >= 82",
    "26*x1 + 7*x3 >= 48",
    "24*x0 + 7*x3 >= 46",
    "25*x2**2 + 14*x4**2 >= 51",
    "26*x1**2 + 25*x2**2 + 14*x4**2 >= 41",
    "24*x0**2 + 26*x1**2 + 25*x2**2 >= 41",
    "24*x0 + 26*x1 + 14*x4 >= 41",
    "26*x1 + 7*x3 + 14*x4 >= 41",
    "24*x0 + 25*x2 + 14*x4 >= 41",
    "24*x0**2 + 26*x1**2 + 7*x3**2 >= 41",
    "26*x1 + 25*x2 + 14*x4 >= 33",
    "24*x0**2 + 26*x1**2 + 25*x2**2 >= 33",
    "24*x0 + 26*x1 + 14*x4 >= 33",
    "26*x1 + 7*x3 + 14*x4 >= 33",
    "24*x0 + 25*x2 + 14*x4 >= 33",
    "24*x0 + 26*x1 + 7*x3 >= 33",
    "26*x1 + 25*x2 + 14*x4 >= 36",
    "24*x0 + 26*x1 + 25*x2 >= 36",
    "24*x0 + 26*x1 + 14*x4 >= 36",
    "26*x1**2 + 7*x3**2 + 14*x4**2 >= 36",
    "24*x0**2 + 25*x2**2 + 14*x4**2 >= 36",
    "24*x0 + 26*x1 + 7*x3 >= 36",
    "26*x1**2 + 25*x2**2 + 14*x4**2 >= 32",
    "24*x0 + 26*x1 + 25*x2 >= 32",
    "24*x0**2 + 26*x1**2 + 14*x4**2 >= 32",
    "26*x1 + 7*x3 + 14*x4 >= 32",
    "24*x0 + 25*x2 + 14*x4 >= 32",
    "24*x0 + 26*x1 + 7*x3 >= 32",
    "-6*x0 + 3*x1 >= 0",
    "-7*x1 + 3*x4 >= 0"
    
  ]
}
```

```python
import gurobipy as gp

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

# Create variables
x0 = m.addVar(vtype=gp.GRB.INTEGER, name="rotisserie_chickens")
x1 = m.addVar(vtype=gp.GRB.INTEGER, name="protein_bars")
x2 = m.addVar(vtype=gp.GRB.INTEGER, name="apples")
x3 = m.addVar(vtype=gp.GRB.CONTINUOUS, name="blueberry_pies")
x4 = m.addVar(vtype=gp.GRB.INTEGER, name="green_beans")


# Set objective function
m.setObjective(9.34*x0**2 + 6.55*x0*x1 + 6.61*x0*x3 + 7.75*x1**2 + 2.23*x2**2 + 7.72*x1, gp.GRB.MINIMIZE)

# Add constraints
m.addConstr(16*x0 + 25*x1 + 15*x2 + 7*x3 + 3*x4 <= 452, "c0")
m.addConstr(24*x0 + 26*x1 + 25*x2 + 7*x3 + 14*x4 <= 308, "c1")
# ... (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("The model is infeasible.")
else:
    print("Optimization ended with status %d" % m.status)

```