```json
{
  "sym_variables": [
    ("x0", "hours worked by Bobby"),
    ("x1", "hours worked by Hank"),
    ("x2", "hours worked by George"),
    ("x3", "hours worked by Paul")
  ],
  "objective_function": "9*x0 + 9*x1 + 9*x2 + 5*x3",
  "constraints": [
    "12.31*x0 + 5.88*x1 >= 27",
    "14.3*x2 + 12.49*x3 >= 27",
    "5.88*x1 + 14.3*x2 >= 30",
    "6.47*x0 + 7.82*x1 + 6.71*x2 >= 40",
    "7.82*x1 + 6.71*x2 + 11.73*x3 >= 40",
    "6.47*x0 + 7.82*x1 + 11.73*x3 >= 40",
    "6.71*x2 + 11.73*x3 >= 14",
    "7.82*x1 + 11.73*x3 >= 24",
    "7.82*x1 + 6.71*x2 + 11.73*x3 >= 22",
    "6.47*x0 + 7.82*x1 + 11.73*x3 >= 22",
    "6.47*x0 + 7.82*x1 + 6.71*x2 >= 22",
    "12.31*x0 + 5.88*x1 <= 68",
    "5.88*x1 + 14.3*x2 <= 76",
    "12.31*x0 + 14.3*x2 <= 99",
    "12.31*x0 + 5.88*x1 + 14.3*x2 + 12.49*x3 <= 99",
    "6.47*x0 + 6.71*x2 <= 65",
    "7.82*x1 + 11.73*x3 <= 141",
    "6.71*x2 + 11.73*x3 <= 123",
    "7.82*x1 + 6.71*x2 + 11.73*x3 <= 145",
    "6.47*x0 + 7.82*x1 + 6.71*x2 + 11.73*x3 <= 145",
    "x0 >= 0",
    "x1 >= 0",
    "x2 >= 0",
    "x3 >= 0"

  ]
}
```

```python
import gurobipy as gp

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

    # Create variables
    x = m.addVars(4, lb=0, vtype=gp.GRB.CONTINUOUS, name=["Bobby", "Hank", "George", "Paul"])


    # Set objective function
    m.setObjective(9*x[0] + 9*x[1] + 9*x[2] + 5*x[3], gp.GRB.MAXIMIZE)

    # Add constraints
    m.addConstr(12.31*x[0] + 5.88*x[1] >= 27)
    m.addConstr(14.3*x[2] + 12.49*x[3] >= 27)
    m.addConstr(5.88*x[1] + 14.3*x[2] >= 30)
    m.addConstr(6.47*x[0] + 7.82*x[1] + 6.71*x[2] >= 40)
    m.addConstr(7.82*x[1] + 6.71*x[2] + 11.73*x[3] >= 40)
    m.addConstr(6.47*x[0] + 7.82*x[1] + 11.73*x[3] >= 40)
    m.addConstr(6.71*x[2] + 11.73*x[3] >= 14)
    m.addConstr(7.82*x[1] + 11.73*x[3] >= 24)
    m.addConstr(7.82*x[1] + 6.71*x[2] + 11.73*x[3] >= 22)
    m.addConstr(6.47*x[0] + 7.82*x[1] + 11.73*x[3] >= 22)
    m.addConstr(6.47*x[0] + 7.82*x[1] + 6.71*x[2] >= 22)
    m.addConstr(12.31*x[0] + 5.88*x[1] <= 68)
    m.addConstr(5.88*x[1] + 14.3*x[2] <= 76)
    m.addConstr(12.31*x[0] + 14.3*x[2] <= 99)
    m.addConstr(12.31*x[0] + 5.88*x[1] + 14.3*x[2] + 12.49*x[3] <= 99)
    m.addConstr(6.47*x[0] + 6.71*x[2] <= 65)
    m.addConstr(7.82*x[1] + 11.73*x[3] <= 141)
    m.addConstr(6.71*x[2] + 11.73*x[3] <= 123)
    m.addConstr(7.82*x[1] + 6.71*x[2] + 11.73*x[3] <= 145)
    m.addConstr(6.47*x[0] + 7.82*x[1] + 6.71*x[2] + 11.73*x[3] <= 145)


    # Optimize model
    m.optimize()

    if m.status == gp.GRB.OPTIMAL:
        for v in m.getVars():
            print(f'{v.varName}: {v.x}')
        print(f'Obj: {m.objVal}')
    elif m.status == gp.GRB.INFEASIBLE:
        print("The model is infeasible.")
    else:
        print(f"Optimization ended with status {m.status}")


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

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