```json
{
  "sym_variables": [
    ("x0", "steaks"),
    ("x1", "cantaloupes"),
    ("x2", "green beans"),
    ("x3", "oreos")
  ],
  "objective_function": "4*x0 + 9*x1 + 9*x2 + 3*x3",
  "constraints": [
    "3*x2 + 12*x3 >= 22",
    "3*x0 + 3*x2 >= 35",
    "3*x0 + 12*x3 >= 34",
    "3*x0 + 2*x1 >= 37",
    "2*x1 + 12*x3 >= 42",
    "2*x1 + 3*x2 >= 32",
    "3*x0 + 3*x2 + 12*x3 >= 47",
    "3*x0 + 2*x1 + 3*x2 >= 47",
    "3*x0 + 3*x2 + 12*x3 >= 52",
    "3*x0 + 2*x1 + 3*x2 >= 52",
    "3*x0 + 2*x1 + 3*x2 + 12*x3 >= 52",
    "2*x1 + 8*x3 >= 9",
    "12*x0 + 8*x3 >= 14",
    "12*x0 + 10*x2 >= 23",
    "12*x0 + 2*x1 >= 15",
    "12*x0 + 2*x1 + 10*x2 + 8*x3 >= 15",
    "-3*x0 + 2*x3 >= 0",
    "9*x0 - 5*x2 >= 0",
    "2*x1 + 3*x2 + 12*x3 <= 133",
    "12*x0 + 2*x1 + 10*x2 <= 32",
    "x0 == int(x0)",
    "x3 == int(x3)"
  ]
}
```

```python
import gurobipy as gp

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

    # Create variables
    steaks = m.addVar(vtype=gp.GRB.INTEGER, name="steaks")
    cantaloupes = m.addVar(vtype=gp.GRB.CONTINUOUS, name="cantaloupes")
    green_beans = m.addVar(vtype=gp.GRB.CONTINUOUS, name="green_beans")
    oreos = m.addVar(vtype=gp.GRB.INTEGER, name="oreos")

    # Set objective function
    m.setObjective(4*steaks + 9*cantaloupes + 9*green_beans + 3*oreos, gp.GRB.MINIMIZE)

    # Add constraints
    m.addConstr(3*green_beans + 12*oreos >= 22)
    m.addConstr(3*steaks + 3*green_beans >= 35)
    m.addConstr(3*steaks + 12*oreos >= 34)
    m.addConstr(3*steaks + 2*cantaloupes >= 37)
    m.addConstr(2*cantaloupes + 12*oreos >= 42)
    m.addConstr(2*cantaloupes + 3*green_beans >= 32)
    m.addConstr(3*steaks + 3*green_beans + 12*oreos >= 47)
    m.addConstr(3*steaks + 2*cantaloupes + 3*green_beans >= 47)
    m.addConstr(3*steaks + 3*green_beans + 12*oreos >= 52)
    m.addConstr(3*steaks + 2*cantaloupes + 3*green_beans >= 52)
    m.addConstr(3*steaks + 2*cantaloupes + 3*green_beans + 12*oreos >= 52)
    m.addConstr(2*cantaloupes + 8*oreos >= 9)
    m.addConstr(12*steaks + 8*oreos >= 14)
    m.addConstr(12*steaks + 10*green_beans >= 23)
    m.addConstr(12*steaks + 2*cantaloupes >= 15)
    m.addConstr(12*steaks + 2*cantaloupes + 10*green_beans + 8*oreos >= 15)
    m.addConstr(-3*steaks + 2*oreos >= 0)
    m.addConstr(9*steaks - 5*green_beans >= 0)
    m.addConstr(2*cantaloupes + 3*green_beans + 12*oreos <= 133)
    m.addConstr(12*steaks + 2*cantaloupes + 10*green_beans <= 32)


    # Optimize model
    m.optimize()

    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.')

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

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