```json
{
  "sym_variables": [
    ("x0", "apple pies"),
    ("x1", "fruit salads"),
    ("x2", "granola bars"),
    ("x3", "apples"),
    ("x4", "chicken drumsticks"),
    ("x5", "oreos")
  ],
  "objective_function": "8.17*x0**2 + 3.12*x0*x1 + 7.03*x0*x3 + 6.42*x0*x4 + 9.3*x0*x5 + 5.5*x1*x3 + 9.41*x1*x5 + 2.68*x1 + 5.89*x2 + 9.05*x3",
  "constraints": [
    "17*x0 + 17*x1 + 12*x2 + 13*x3 + 14*x4 + 14*x5 <= 262",
    "10*x0 + 2*x1 + 12*x2 + 10*x3 + 13*x4 + 8*x5 <= 293",
    "15*x0 + 15*x1 + 7*x2 + 12*x3 + 14*x4 + 3*x5 <= 213",
    "5*x0 + 8*x1 + 8*x2 + 11*x3 + 8*x4 + 15*x5 <= 213",
    "6*x0 + 17*x1 + 6*x2 + 1*x3 + 9*x4 + 11*x5 <= 325",
    "x2**2 + x4**2 >= 35",
    "x0**2 + x3**2 >= 15",
    "x0 + x5 >= 25",
    "x1**2 + x5**2 >= 39",
    "x2 + x3 >= 20",
    "x0 + x4 + x5 >= 33",
    "x0 + x2 + x3 >= 33",
    "x1**2 + x2**2 + x4**2 >= 33",
    "x0 + x1 + x3 >= 33",
    "x0**2 + x2**2 + x4**2 >= 33",
    "x1 + x2 + x5 >= 33",
    "x1 + x2 + x3 >= 33",
    "x0**2 + x3**2 + x5**2 >= 33",
    "x3**2 + x4**2 + x5**2 >= 33",
    "x1 + x3 + x5 >= 33",
    "x2 + x4 + x5 >= 33",
    "x0**2 + x4**2 + x5**2 >= 31",
    "x0 + x2 + x3 >= 31",
    "x1 + x2 + x4 >= 31",
    "x0**2 + x1**2 + x3**2 >= 31",
    "x0 + x2 + x4 >= 31",
    "x1 + x2 + x5 >= 31",
    "x1 + x2 + x3 >= 31",
    "x0**2 + x3**2 + x5**2 >= 31",
    "x3**2 + x4**2 + x5**2 >= 31",
    "x1 + x3 + x5 >= 31",
    "x2 + x4 + x5 >= 31",
    "x0 + x4 + x5 >= 27",
    "x0**2 + x2**2 + x3**2 >= 27",
    "x1**2 + x2**2 + x4**2 >= 27",
    "x0 + x1 + x3 >= 27",
    "x0 + x2 + x4 >= 27",
    "x1**2 + x2**2 + x5**2 >= 27",
    "x1**2 + x2**2 + x3**2 >= 27",
    "x0 + x3 + x5 >= 27",
    "x3 + x4 + x5 >= 27",
    "x1 + x3 + x5 >= 27",
    "x2**2 + x4**2 + x5**2 >= 27",
    "-3*x1**2 + 9*x4**2 >= 0", 
    "x0**2 + x1**2 + x4**2 <= 130",
    "x2 + x3 + x4 <= 245",
    "x1 + x2 + x3 <= 76",
    "x1 + x3 + x4 <= 172",
    "x2 + x4 + x5 <= 101",
    "x1 + x3 + x5 <= 67"
  ]
}
```

```python
import gurobipy as gp

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

# Create variables
x = m.addVars(6, lb=0, vtype=gp.GRB.CONTINUOUS, name=["apple pies", "fruit salads", "granola bars", "apples", "chicken drumsticks", "oreos"])


# Set objective function
m.setObjective(8.17*x[0]**2 + 3.12*x[0]*x[1] + 7.03*x[0]*x[3] + 6.42*x[0]*x[4] + 9.3*x[0]*x[5] + 5.5*x[1]*x[3] + 9.41*x[1]*x[5] + 2.68*x[1] + 5.89*x[2] + 9.05*x[3], gp.GRB.MINIMIZE)

# Add constraints
m.addConstr(17*x[0] + 17*x[1] + 12*x[2] + 13*x[3] + 14*x[4] + 14*x[5] <= 262, "r0")
m.addConstr(10*x[0] + 2*x[1] + 12*x[2] + 10*x[3] + 13*x[4] + 8*x[5] <= 293, "r1")
m.addConstr(15*x[0] + 15*x[1] + 7*x[2] + 12*x[3] + 14*x[4] + 3*x[5] <= 213, "r2")
m.addConstr(5*x[0] + 8*x[1] + 8*x[2] + 11*x[3] + 8*x[4] + 15*x[5] <= 213, "r3")
m.addConstr(6*x[0] + 17*x[1] + 6*x[2] + 1*x[3] + 9*x[4] + 11*x[5] <= 325, "r4")
# ... (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 problem is infeasible.")
else:
    print("Optimization terminated with status:", m.status)

```