```json
{
  "sym_variables": [
    ("x0", "ravioli"),
    ("x1", "rotisserie chickens")
  ],
  "objective_function": "5.73*x0**2 + 1.63*x1",
  "constraints": [
    "4*x0 + 18*x1 <= 173",  // healthiness rating
    "19*x0 + 4*x1 <= 225",   // grams of protein
    "7*x0 + 25*x1 <= 122",   // sourness index
    "16*x0 + 23*x1 <= 245",   // grams of fiber
    "15*x0 + 7*x1 <= 207",   // milligrams of iron
    "x0**2 + x1**2 >= 57",      // combined healthiness rating
    "19*x0 + 4*x1 >= 67",    // combined grams of protein
    "7*x0 + 25*x1 >= 47",    // combined sourness index
    "16*x0**2 + 23*x1**2 >= 108", // combined grams of fiber
    "15*x0 + 7*x1 >= 65",    // combined milligrams of iron
    "-9*x0 + 2*x1 >= 0",
    "4*x0 + 18*x1 <= 100",  // combined healthiness rating
    "19*x0 + 4*x1 <= 158",   // combined grams of protein
    "7*x0 + 25*x1 <= 119",   // combined sourness index
    "16*x0 + 23*x1 <= 197",   // combined grams of fiber
    "15*x0 + 7*x1 <= 149"    // combined milligrams of iron
  ]
}
```

```python
import gurobipy as gp

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

    # Create variables
    ravioli = m.addVar(vtype=gp.GRB.INTEGER, name="ravioli")
    rotisserie_chickens = m.addVar(vtype=gp.GRB.CONTINUOUS, name="rotisserie_chickens")

    # Set objective function
    m.setObjective(5.73 * ravioli**2 + 1.63 * rotisserie_chickens, gp.GRB.MAXIMIZE)

    # Add constraints
    m.addConstr(4 * ravioli + 18 * rotisserie_chickens <= 173, "c0")
    m.addConstr(19 * ravioli + 4 * rotisserie_chickens <= 225, "c1")
    m.addConstr(7 * ravioli + 25 * rotisserie_chickens <= 122, "c2")
    m.addConstr(16 * ravioli + 23 * rotisserie_chickens <= 245, "c3")
    m.addConstr(15 * ravioli + 7 * rotisserie_chickens <= 207, "c4")
    m.addConstr(ravioli**2 + rotisserie_chickens**2 >= 57, "c5")
    m.addConstr(19 * ravioli + 4 * rotisserie_chickens >= 67, "c6")
    m.addConstr(7 * ravioli + 25 * rotisserie_chickens >= 47, "c7")
    m.addConstr(16 * ravioli**2 + 23 * rotisserie_chickens**2 >= 108, "c8")
    m.addConstr(15 * ravioli + 7 * rotisserie_chickens >= 65, "c9")
    m.addConstr(-9 * ravioli + 2 * rotisserie_chickens >= 0, "c10")
    m.addConstr(4 * ravioli + 18 * rotisserie_chickens <= 100, "c11")
    m.addConstr(19 * ravioli + 4 * rotisserie_chickens <= 158, "c12")
    m.addConstr(7 * ravioli + 25 * rotisserie_chickens <= 119, "c13")
    m.addConstr(16 * ravioli + 23 * rotisserie_chickens <= 197, "c14")
    m.addConstr(15 * ravioli + 7 * rotisserie_chickens <= 149, "c15")


    # Optimize model
    m.optimize()

    if m.status == gp.GRB.OPTIMAL:
        print('Obj: %g' % m.objVal)
        print('ravioli:', ravioli.x)
        print('rotisserie_chickens:', rotisserie_chickens.x)
    elif m.status == gp.GRB.INFEASIBLE:
        print('The 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')
```
