```json
{
  "sym_variables": [
    ("x0", "apples"),
    ("x1", "eggs"),
    ("x2", "bowls of instant ramen")
  ],
  "objective_function": "9.29*x0**2 + 3.05*x0*x1 + 9.45*x1*x2 + 7.93*x0 + 6.27*x1 + 8.08*x2",
  "constraints": [
    "0.43*x1 + 2.94*x2 >= 31",
    "2.67*x0**2 + 2.94*x2**2 >= 16",
    "0.43*x1**2 + 2.94*x2**2 <= 97",
    "2.67*x0 + 0.43*x1 <= 90",
    "2.67*x0 + 0.43*x1 + 2.94*x2 <= 90"
  ]
}
```

```python
import gurobipy as gp
from gurobipy import GRB

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

    # Create variables
    apples = m.addVar(lb=0, name="apples")
    eggs = m.addVar(lb=0, name="eggs")
    ramen = m.addVar(lb=0, name="ramen")


    # Set objective function
    m.setObjective(9.29*apples**2 + 3.05*apples*eggs + 9.45*eggs*ramen + 7.93*apples + 6.27*eggs + 8.08*ramen, GRB.MAXIMIZE)

    # Add constraints
    m.addConstr(0.43*eggs + 2.94*ramen >= 31, "fiber_constraint1")
    m.addConstr(2.67*apples**2 + 2.94*ramen**2 >= 16, "fiber_constraint2")
    m.addConstr(0.43*eggs**2 + 2.94*ramen**2 <= 97, "fiber_constraint3")
    m.addConstr(2.67*apples + 0.43*eggs <= 90, "fiber_constraint4")
    m.addConstr(2.67*apples + 0.43*eggs + 2.94*ramen <= 90, "fiber_constraint5")


    # Optimize model
    m.optimize()

    # Check for infeasibility
    if m.status == GRB.INFEASIBLE:
        print("The model is infeasible.")
    else:
        # Print optimal solution
        print("Optimal objective value:", m.objVal)
        print("Apples:", apples.x)
        print("Eggs:", eggs.x)
        print("Bowls of instant ramen:", ramen.x)


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

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