```json
{
  "sym_variables": [
    ("x0", "cornichons"),
    ("x1", "bowls of pasta"),
    ("x2", "corn cobs"),
    ("x3", "cantaloupes")
  ],
  "objective_function": "7*x0 + 9*x1 + 2*x2 + 8*x3",
  "constraints": [
    "3.56*x2 + 0.04*x3 >= 31",
    "6.09*x1 + 3.56*x2 + 0.04*x3 >= 37",
    "3.85*x0 + 3.56*x2 + 0.04*x3 >= 37",
    "3.85*x0 + 6.09*x1 + 0.04*x3 >= 37",
    "6.09*x1 + 3.56*x2 + 0.04*x3 >= 20",
    "3.85*x0 + 3.56*x2 + 0.04*x3 >= 20",
    "3.85*x0 + 6.09*x1 + 0.04*x3 >= 20",
    "6.09*x1 + 3.56*x2 + 0.04*x3 >= 34",
    "3.85*x0 + 3.56*x2 + 0.04*x3 >= 34",
    "3.85*x0 + 6.09*x1 + 0.04*x3 >= 34",
    "6.02*x0 + 2.73*x2 >= 13",
    "6.02*x0 + 2.51*x3 >= 11",
    "6.74*x1 + 2.73*x2 >= 9",
    "3.85*x0 + 6.09*x1 <= 69",
    "3.85*x0 + 0.04*x3 <= 104",
    "3.85*x0 + 3.56*x2 <= 102",
    "6.09*x1 + 0.04*x3 <= 78",
    "6.09*x1 + 3.56*x2 <= 54",
    "3.85*x0 + 6.09*x1 + 3.56*x2 <= 69",
    "3.85*x0 + 6.09*x1 + 3.56*x2 + 0.04*x3 <= 69",
    "6.02*x0 + 2.73*x2 <= 50",
    "6.02*x0 + 6.74*x1 <= 35",
    "6.74*x1 + 2.51*x3 <= 65",
    "6.02*x0 + 2.73*x2 + 2.51*x3 <= 42",
    "6.02*x0 + 6.74*x1 + 2.73*x2 + 2.51*x3 <= 42",
    "x0 >= 0",
    "x1 >= 0",
    "x2 >= 0",
    "x3 >= 0"
  ]
}
```

```python
import gurobipy as gp

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

# Create variables
cornichons = m.addVar(lb=0, vtype=gp.GRB.CONTINUOUS, name="cornichons")
bowls_of_pasta = m.addVar(lb=0, vtype=gp.GRB.CONTINUOUS, name="bowls_of_pasta")
corn_cobs = m.addVar(lb=0, vtype=gp.GRB.CONTINUOUS, name="corn_cobs")
cantaloupes = m.addVar(lb=0, vtype=gp.GRB.CONTINUOUS, name="cantaloupes")

# Set objective function
m.setObjective(7 * cornichons + 9 * bowls_of_pasta + 2 * corn_cobs + 8 * cantaloupes, gp.GRB.MAXIMIZE)

# Add constraints
m.addConstr(3.56 * corn_cobs + 0.04 * cantaloupes >= 31)
m.addConstr(6.09 * bowls_of_pasta + 3.56 * corn_cobs + 0.04 * cantaloupes >= 37)
m.addConstr(3.85 * cornichons + 3.56 * corn_cobs + 0.04 * cantaloupes >= 37)
m.addConstr(3.85 * cornichons + 6.09 * bowls_of_pasta + 0.04 * cantaloupes >= 37)
m.addConstr(6.09 * bowls_of_pasta + 3.56 * corn_cobs + 0.04 * cantaloupes >= 20)
m.addConstr(3.85 * cornichons + 3.56 * corn_cobs + 0.04 * cantaloupes >= 20)
m.addConstr(3.85 * cornichons + 6.09 * bowls_of_pasta + 0.04 * cantaloupes >= 20)
m.addConstr(6.09 * bowls_of_pasta + 3.56 * corn_cobs + 0.04 * cantaloupes >= 34)
m.addConstr(3.85 * cornichons + 3.56 * corn_cobs + 0.04 * cantaloupes >= 34)
m.addConstr(3.85 * cornichons + 6.09 * bowls_of_pasta + 0.04 * cantaloupes >= 34)
m.addConstr(6.02 * cornichons + 2.73 * corn_cobs >= 13)
m.addConstr(6.02 * cornichons + 2.51 * cantaloupes >= 11)
m.addConstr(6.74 * bowls_of_pasta + 2.73 * corn_cobs >= 9)
m.addConstr(3.85 * cornichons + 6.09 * bowls_of_pasta <= 69)
m.addConstr(3.85 * cornichons + 0.04 * cantaloupes <= 104)
m.addConstr(3.85 * cornichons + 3.56 * corn_cobs <= 102)
m.addConstr(6.09 * bowls_of_pasta + 0.04 * cantaloupes <= 78)
m.addConstr(6.09 * bowls_of_pasta + 3.56 * corn_cobs <= 54)
m.addConstr(3.85 * cornichons + 6.09 * bowls_of_pasta + 3.56 * corn_cobs <= 69)
m.addConstr(3.85 * cornichons + 6.09 * bowls_of_pasta + 3.56 * corn_cobs + 0.04 * cantaloupes <= 69)
m.addConstr(6.02 * cornichons + 2.73 * corn_cobs <= 50)
m.addConstr(6.02 * cornichons + 6.74 * bowls_of_pasta <= 35)
m.addConstr(6.74 * bowls_of_pasta + 2.51 * cantaloupes <= 65)
m.addConstr(6.02 * cornichons + 2.73 * corn_cobs + 2.51 * cantaloupes <= 42)
m.addConstr(6.02 * cornichons + 6.74 * bowls_of_pasta + 2.73 * corn_cobs + 2.51 * cantaloupes <= 42)


# Optimize model
m.optimize()

# Print results
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("The problem is infeasible.")
else:
    print("The problem could not be solved to optimality.")

```
