## Step 1: Define the variables and their attributes
We have four variables: 'knishes', 'ravioli', 'cantaloupes', and 'chicken thighs'. Each variable has attributes related to milligrams of calcium and grams of fat. The attributes are as follows:
- 'r0': milligrams of calcium with an upper bound of 130.
  - 'knishes': 10.29 mg
  - 'ravioli': 8.15 mg
  - 'cantaloupes': 5.24 mg
  - 'chicken thighs': 4.29 mg
- 'r1': grams of fat with an upper bound of 87.
  - 'knishes': 1.94 g
  - 'ravioli': 8.63 g
  - 'cantaloupes': 9.01 g
  - 'chicken thighs': 4.03 g

## Step 2: Formulate the objective function
The objective function to minimize is:
\[ 3.6 \times (\text{knishes})^2 + 8.76 \times \text{knishes} \times \text{ravioli} + 8.77 \times \text{knishes} \times \text{cantaloupes} + 5.38 \times \text{knishes} \times \text{chicken thighs} + 5.13 \times (\text{cantaloupes})^2 \]

## 3: Define the constraints
### Calcium Constraints
1. \( 10.29 \times \text{knishes} \leq 130 \)
2. \( 8.15 \times \text{ravioli} \leq 130 \)
3. \( 5.24 \times \text{cantaloupes} \leq 130 \)
4. \( 4.29 \times \text{chicken thighs} \leq 130 \)
5. \( 10.29^2 \times (\text{knishes})^2 + 5.24^2 \times (\text{cantaloupes})^2 \geq 24 \)
6. \( 5.24^2 \times (\text{cantaloupes})^2 + 4.29^2 \times (\text{chicken thighs})^2 \geq 29 \)
7. \( 10.29 \times \text{knishes} + 4.29 \times \text{chicken thighs} \geq 21 \)
8. \( 8.15 \times \text{ravioli} + 5.24 \times \text{cantaloupes} \geq 30 \)
9. \( 10.29 \times \text{knishes} + 8.15 \times \text{ravioli} + 5.24 \times \text{cantaloupes} + 4.29 \times \text{chicken thighs} \geq 30 \)
10. \( 5.24 \times \text{cantaloupes} + 4.29 \times \text{chicken thighs} \leq 63 \)
11. \( 10.29 \times \text{knishes} + 4.29 \times \text{chicken thighs} \leq 72 \)

### Fat Constraints
12. \( 1.94 \times \text{knishes} \leq 87 \)
13. \( 8.63 \times \text{ravioli} \leq 87 \)
14. \( 9.01 \times \text{cantaloupes} \leq 87 \)
15. \( 4.03 \times \text{chicken thighs} \leq 87 \)
16. \( 1.94 \times \text{knishes} + 9.01 \times \text{cantaloupes} \geq 18 \)
17. \( 8.63 \times \text{ravioli} + 9.01 \times \text{cantaloupes} \geq 19 \)
18. \( 1.94 \times \text{knishes} + 8.63 \times \text{ravioli} \geq 13 \)
19. \( 1.94^2 \times (\text{knishes})^2 + 4.03^2 \times (\text{chicken thighs})^2 \geq 20 \)
20. \( 8.63 \times \text{ravioli} + 9.01 \times \text{cantaloupes} + 4.03 \times \text{chicken thighs} \geq 20 \)
21. \( 1.94 \times \text{knishes} + 8.63 \times \text{ravioli} + 9.01 \times \text{cantaloupes} + 4.03 \times \text{chicken thighs} \geq 20 \)
22. \( 8.63^2 \times (\text{ravioli})^2 + 4.03^2 \times (\text{chicken thighs})^2 \leq 42 \)
23. \( 1.94 \times \text{knishes} + 8.63 \times \text{ravioli} + 4.03 \times \text{chicken thighs} \leq 74 \)
24. \( 1.94 \times \text{knishes} + 8.63 \times \text{ravioli} + 9.01 \times \text{cantaloupes} \leq 62 \)
25. \( 1.94 \times \text{knishes} + 9.01 \times \text{cantaloupes} + 4.03 \times \text{chicken thighs} \leq 45 \)

### Linear Constraints
26. \( -3 \times \text{knishes} + 2 \times \text{ravioli} \geq 0 \)

## 4: Implement the problem in Gurobi
```python
import gurobi

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

    # Define the variables
    knishes = model.addVar(name="knishes", lb=0)
    ravioli = model.addVar(name="ravioli", lb=0)
    cantaloupes = model.addVar(name="cantaloupes", lb=0)
    chicken_thighs = model.addVar(name="chicken_thighs", lb=0)

    # Objective function
    model.setObjective(3.6 * knishes**2 + 8.76 * knishes * ravioli + 8.77 * knishes * cantaloupes + 5.38 * knishes * chicken_thighs + 5.13 * cantaloupes**2, gurobi.GRB.MINIMIZE)

    # Constraints
    # Calcium constraints
    model.addConstr(10.29 * knishes <= 130)
    model.addConstr(8.15 * ravioli <= 130)
    model.addConstr(5.24 * cantaloupes <= 130)
    model.addConstr(4.29 * chicken_thighs <= 130)
    model.addConstr(10.29**2 * knishes**2 + 5.24**2 * cantaloupes**2 >= 24)
    model.addConstr(5.24**2 * cantaloupes**2 + 4.29**2 * chicken_thighs**2 >= 29)
    model.addConstr(10.29 * knishes + 4.29 * chicken_thighs >= 21)
    model.addConstr(8.15 * ravioli + 5.24 * cantaloupes >= 30)
    model.addConstr(10.29 * knishes + 8.15 * ravioli + 5.24 * cantaloupes + 4.29 * chicken_thighs >= 30)
    model.addConstr(5.24 * cantaloupes + 4.29 * chicken_thighs <= 63)
    model.addConstr(10.29 * knishes + 4.29 * chicken_thighs <= 72)

    # Fat constraints
    model.addConstr(1.94 * knishes <= 87)
    model.addConstr(8.63 * ravioli <= 87)
    model.addConstr(9.01 * cantaloupes <= 87)
    model.addConstr(4.03 * chicken_thighs <= 87)
    model.addConstr(1.94 * knishes + 9.01 * cantaloupes >= 18)
    model.addConstr(8.63 * ravioli + 9.01 * cantaloupes >= 19)
    model.addConstr(1.94 * knishes + 8.63 * ravioli >= 13)
    model.addConstr(1.94**2 * knishes**2 + 4.03**2 * chicken_thighs**2 >= 20)
    model.addConstr(8.63 * ravioli + 9.01 * cantaloupes + 4.03 * chicken_thighs >= 20)
    model.addConstr(1.94 * knishes + 8.63 * ravioli + 9.01 * cantaloupes + 4.03 * chicken_thighs >= 20)
    model.addConstr(8.63**2 * ravioli**2 + 4.03**2 * chicken_thighs**2 <= 42)
    model.addConstr(1.94 * knishes + 8.63 * ravioli + 4.03 * chicken_thighs <= 74)
    model.addConstr(1.94 * knishes + 8.63 * ravioli + 9.01 * cantaloupes <= 62)
    model.addConstr(1.94 * knishes + 9.01 * cantaloupes + 4.03 * chicken_thighs <= 45)

    # Linear constraint
    model.addConstr(-3 * knishes + 2 * ravioli >= 0)

    # Optimize the model
    model.optimize()

    # Print the solution
    if model.status == gurobi.GRB.OPTIMAL:
        print("Objective: ", model.objval)
        print("Knishes: ", knishes.varValue)
        print("Ravioli: ", ravioli.varValue)
        print("Cantaloupes: ", cantaloupes.varValue)
        print("Chicken Thighs: ", chicken_thighs.varValue)
    else:
        print("The model is infeasible")

optimize_problem()
```