To solve this optimization problem, we first need to define the variables, objective function, and constraints using Gurobi's Python interface.

## Step 1: Define the Variables
Let's define the variables for the hours worked by each person: George (G), Jean (J), Dale (D), Ringo (R), and Bill (B).

## Step 2: Define the Objective Function
The objective function to maximize is: $1G + 4J + 2D + 4R + 8B$.

## 3: Define the Constraints
We have the following constraints:
1. $3.93R + 2.49B \geq 18$
2. $4.64D + 2.49B \geq 41$
3. $1.38J + 3.93R + 2.49B \geq 47$
4. $1.38J + 4.64D + 2.49B \geq 47$
5. $1.38J + 3.93R + 2.49B \geq 43$
6. $1.38J + 4.64D + 2.49B \geq 43$
7. $3.74J + 1.07B \geq 12$
8. $5.04G + 3.74J \geq 15$
9. $3.74J + 5.86R \geq 14$
10. $0.56D + 1.07B \geq 14$
11. $5.04G + 0.56D \geq 10$
12. $5.04G + 0.56D + 1.07B \geq 16$
13. $3.93R + 2.49B \leq 129$
14. $1.29G + 1.38J \leq 207$
15. $4.64D + 3.93R \leq 214$
16. $1.29G + 1.38J + 4.64D + 3.93R + 2.49B \leq 214$
17. $5.04G + 3.74J \leq 94$
18. $3.74J + 1.07B \leq 149$
19. $5.04G + 1.07B \leq 86$
20. $3.74J + 0.56D \leq 124$
21. $5.04G + 5.86R \leq 82$
22. $5.86R + 1.07B \leq 84$
23. $0.56D + 1.07B \leq 87$
24. $5.04G + 3.74J + 0.56D + 5.86R + 1.07B \leq 87$
25. $5.22G + 4.63B \leq 27$
26. $1.67J + 2.74R \leq 79$
27. $1.67J + 3.29D + 4.63B \leq 85$
28. $1.67J + 3.29D + 2.74R \leq 45$
29. $5.22G + 1.67J + 3.29D \leq 51$
30. $5.22G + 2.74R + 4.63B \leq 66$
31. $5.22G + 3.29D + 4.63B \leq 54$
32. $1.67J + 2.74R + 4.63B \leq 67$
33. $5.22G + 1.67J + 2.74R \leq 81$
34. $3.29D + 2.74R + 4.63B \leq 42$
35. $5.22G + 1.67J + 3.29D + 2.74R + 4.63B \leq 42$

## 4: Implement in Gurobi
Now, let's implement this in Gurobi:

```python
import gurobi

def optimize_problem():
    # Create a new model
    model = gurobi.Model()

    # Define the variables
    G = model.addVar(name="George", lb=0)
    J = model.addVar(name="Jean", lb=0)
    D = model.addVar(name="Dale", lb=0)
    R = model.addVar(name="Ringo", lb=0)
    B = model.addVar(name="Bill", lb=0)

    # Define the objective function
    model.setObjective(G + 4 * J + 2 * D + 4 * R + 8 * B, gurobi.GRB.MAXIMIZE)

    # Add constraints
    model.addConstr(3.93 * R + 2.49 * B >= 18)
    model.addConstr(4.64 * D + 2.49 * B >= 41)
    model.addConstr(1.38 * J + 3.93 * R + 2.49 * B >= 47)
    model.addConstr(1.38 * J + 4.64 * D + 2.49 * B >= 47)
    model.addConstr(1.38 * J + 3.93 * R + 2.49 * B >= 43)
    model.addConstr(1.38 * J + 4.64 * D + 2.49 * B >= 43)
    model.addConstr(3.74 * J + 1.07 * B >= 12)
    model.addConstr(5.04 * G + 3.74 * J >= 15)
    model.addConstr(3.74 * J + 5.86 * R >= 14)
    model.addConstr(0.56 * D + 1.07 * B >= 14)
    model.addConstr(5.04 * G + 0.56 * D >= 10)
    model.addConstr(5.04 * G + 0.56 * D + 1.07 * B >= 16)
    model.addConstr(3.93 * R + 2.49 * B <= 129)
    model.addConstr(1.29 * G + 1.38 * J <= 207)
    model.addConstr(4.64 * D + 3.93 * R <= 214)
    model.addConstr(1.29 * G + 1.38 * J + 4.64 * D + 3.93 * R + 2.49 * B <= 214)
    model.addConstr(5.04 * G + 3.74 * J <= 94)
    model.addConstr(3.74 * J + 1.07 * B <= 149)
    model.addConstr(5.04 * G + 1.07 * B <= 86)
    model.addConstr(3.74 * J + 0.56 * D <= 124)
    model.addConstr(5.04 * G + 5.86 * R <= 82)
    model.addConstr(5.86 * R + 1.07 * B <= 84)
    model.addConstr(0.56 * D + 1.07 * B <= 87)
    model.addConstr(5.04 * G + 3.74 * J + 0.56 * D + 5.86 * R + 1.07 * B <= 87)
    model.addConstr(5.22 * G + 4.63 * B <= 27)
    model.addConstr(1.67 * J + 2.74 * R <= 79)
    model.addConstr(1.67 * J + 3.29 * D + 4.63 * B <= 85)
    model.addConstr(1.67 * J + 3.29 * D + 2.74 * R <= 45)
    model.addConstr(5.22 * G + 1.67 * J + 3.29 * D <= 51)
    model.addConstr(5.22 * G + 2.74 * R + 4.63 * B <= 66)
    model.addConstr(5.22 * G + 3.29 * D + 4.63 * B <= 54)
    model.addConstr(1.67 * J + 2.74 * R + 4.63 * B <= 67)
    model.addConstr(5.22 * G + 1.67 * J + 2.74 * R <= 81)
    model.addConstr(3.29 * D + 2.74 * R + 4.63 * B <= 42)
    model.addConstr(5.22 * G + 1.67 * J + 3.29 * D + 2.74 * R + 4.63 * B <= 42)

    # Solve the model
    model.optimize()

    # Print the solution
    if model.status == gurobi.GRB.OPTIMAL:
        print("Objective: ", model.objVal)
        print("George: ", G.varValue)
        print("Jean: ", J.varValue)
        print("Dale: ", D.varValue)
        print("Ringo: ", R.varValue)
        print("Bill: ", B.varValue)
    else:
        print("No solution found")

optimize_problem()
```