## Step 1: Define the optimization problem
The problem is to maximize the objective function: $2 \times \text{oranges} + 9 \times \text{fruit salads} + 9 \times \text{bowls of cereal}$, subject to various constraints on the resources/attributes 'r0' (grams of carbohydrates), 'r1' (milligrams of iron), 'r2' (umami index), and 'r3' (milligrams of calcium).

## Step 2: List all the constraints
1. $4 \times \text{oranges} + 1 \times \text{fruit salads} + 4 \times \text{bowls of cereal} \leq 84$ (carbohydrates)
2. $1 \times \text{oranges} + 8 \times \text{fruit salads} + 2 \times \text{bowls of cereal} \leq 65$ (iron)
3. $8 \times \text{oranges} + 7 \times \text{fruit salads} + 1 \times \text{bowls of cereal} \leq 68$ (umami index)
4. $2 \times \text{oranges} + 6 \times \text{fruit salads} + 8 \times \text{bowls of cereal} \leq 85$ (calcium)
5. $4 \times \text{oranges} + 4 \times \text{bowls of cereal} \geq 26$ (carbohydrates from oranges and bowls of cereal)
6. $1 \times \text{oranges} + 2 \times \text{bowls of cereal} \geq 13$ (iron from oranges and bowls of cereal)
7. $1 \times \text{oranges} + 8 \times \text{fruit salads} + 2 \times \text{bowls of cereal} \geq 18$ (iron from all sources)
8. $7 \times \text{fruit salads} + 1 \times \text{bowls of cereal} \geq 19$ (umami index from fruit salads and bowls of cereal)
9. $8 \times \text{oranges} + 1 \times \text{bowls of cereal} \geq 11$ (umami index from oranges and bowls of cereal)
10. $4 \times \text{oranges} + 1 \times \text{fruit salads} \leq 54$ (carbohydrates from oranges and fruit salads)
11. $4 \times \text{oranges} + 4 \times \text{bowls of cereal} \leq 58$ (carbohydrates from oranges and bowls of cereal)
12. $4 \times \text{oranges} + 1 \times \text{fruit salads} + 4 \times \text{bowls of cereal} \leq 58$ (carbohydrates from all sources)
13. $1 \times \text{oranges} + 8 \times \text{fruit salads} \leq 62$ (iron from oranges and fruit salads)
14. $1 \times \text{oranges} + 2 \times \text{bowls of cereal} \leq 49$ (iron from oranges and bowls of cereal)
15. $1 \times \text{oranges} + 8 \times \text{fruit salads} + 2 \times \text{bowls of cereal} \leq 49$ (iron from all sources)
16. $8 \times \text{oranges} + 7 \times \text{fruit salads} \leq 60$ (umami index from oranges and fruit salads)
17. $8 \times \text{oranges} + 1 \times \text{bowls of cereal} \leq 34$ (umami index from oranges and bowls of cereal)
18. $7 \times \text{fruit salads} + 1 \times \text{bowls of cereal} \leq 39$ (umami index from fruit salads and bowls of cereal)
19. $8 \times \text{oranges} + 7 \times \text{fruit salads} + 1 \times \text{bowls of cereal} \leq 39$ (umami index from all sources)
20. $2 \times \text{oranges} + 8 \times \text{bowls of cereal} \leq 80$ (calcium from oranges and bowls of cereal)
21. $2 \times \text{oranges} + 6 \times \text{fruit salads} + 8 \times \text{bowls of cereal} \leq 80$ (calcium from all sources)

## Step 3: Implement the optimization problem using Gurobi
```python
import gurobi as gp

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

# Define the variables
oranges = m.addVar(lb=0, name="oranges")
fruit_salads = m.addVar(lb=0, name="fruit_salads")
bowls_of_cereal = m.addVar(lb=0, name="bowls_of_cereal")

# Define the objective function
m.setObjective(2 * oranges + 9 * fruit_salads + 9 * bowls_of_cereal, gp.GRB.MAXIMIZE)

# Define the constraints
m.addConstr(4 * oranges + 1 * fruit_salads + 4 * bowls_of_cereal <= 84)  # r0
m.addConstr(1 * oranges + 8 * fruit_salads + 2 * bowls_of_cereal <= 65)  # r1
m.addConstr(8 * oranges + 7 * fruit_salads + 1 * bowls_of_cereal <= 68)  # r2
m.addConstr(2 * oranges + 6 * fruit_salads + 8 * bowls_of_cereal <= 85)  # r3
m.addConstr(4 * oranges + 4 * bowls_of_cereal >= 26)
m.addConstr(1 * oranges + 2 * bowls_of_cereal >= 13)
m.addConstr(1 * oranges + 8 * fruit_salads + 2 * bowls_of_cereal >= 18)
m.addConstr(7 * fruit_salads + 1 * bowls_of_cereal >= 19)
m.addConstr(8 * oranges + 1 * bowls_of_cereal >= 11)
m.addConstr(4 * oranges + 1 * fruit_salads <= 54)
m.addConstr(4 * oranges + 4 * bowls_of_cereal <= 58)
m.addConstr(4 * oranges + 1 * fruit_salads + 4 * bowls_of_cereal <= 58)
m.addConstr(1 * oranges + 8 * fruit_salads <= 62)
m.addConstr(1 * oranges + 2 * bowls_of_cereal <= 49)
m.addConstr(1 * oranges + 8 * fruit_salads + 2 * bowls_of_cereal <= 49)
m.addConstr(8 * oranges + 7 * fruit_salads <= 60)
m.addConstr(8 * oranges + 1 * bowls_of_cereal <= 34)
m.addConstr(7 * fruit_salads + 1 * bowls_of_cereal <= 39)
m.addConstr(8 * oranges + 7 * fruit_salads + 1 * bowls_of_cereal <= 39)
m.addConstr(2 * oranges + 8 * bowls_of_cereal <= 80)
m.addConstr(2 * oranges + 6 * fruit_salads + 8 * bowls_of_cereal <= 80)

# Solve the model
m.optimize()

# Print the solution
if m.status == gp.GRB.OPTIMAL:
    print("Objective: ", m.objVal)
    print("oranges: ", oranges.varValue)
    print("fruit salads: ", fruit_salads.varValue)
    print("bowls of cereal: ", bowls_of_cereal.varValue)
else:
    print("The model is infeasible")
```