To solve this problem, let's first define the symbolic representation of the optimization problem.

```json
{
    'sym_variables': [
        ('x1', 'cantaloupes'), 
        ('x2', 'chicken drumsticks'), 
        ('x3', 'tomatoes'), 
        ('x4', 'bowls of cereal'), 
        ('x5', 'bowls of pasta'), 
        ('x6', 'bowls of instant ramen'), 
        ('x7', 'corn cobs')
    ], 
    'objective_function': '5*x1 + 2*x2 + 8*x3 + 9*x4 + 9*x5 + 1*x6 + 2*x7', 
    'constraints': [
        '7*x1 + 9*x2 + 6*x3 + 10*x4 + 10*x5 + 9*x6 + 11*x7 <= 304',
        'x4 + x7 >= 32',
        'x4 + x5 >= 15',
        'x3 + x7 >= 24',
        'x5 + x7 >= 26',
        'x4 + x6 >= 28',
        'x3 + x5 >= 15',
        'x1 + x3 >= 23',
        'x5 + x6 >= 24',
        'x1 + x5 >= 32',
        'x1 + x2 >= 40',
        'x3 + x5 + x6 >= 32',
        'x1 + x3 + x7 >= 32',
        'x1 + x2 + x4 >= 32',
        'x3 + x5 + x7 >= 32',
        'x1 + x6 + x7 >= 32',
        'x2 + x3 + x4 >= 32',
        'x1 + x2 + x6 >= 32',
        'x1 + x4 + x6 >= 32',
        'x1 + x4 + x5 >= 32',
        'x4 + x6 + x7 >= 32',
        'x4 + x5 + x6 >= 32',
        'x1 + x2 + x5 >= 32',
        'x5 + x6 + x7 >= 32',
        'x2 + x4 + x5 >= 32',
        'x1 + x3 + x4 >= 32',
        'x2 + x3 + x7 >= 32',
        'x1 + x5 + x6 >= 32',
        'x2 + x6 + x7 >= 32',
        'x4 + x5 + x7 >= 32',
        'x1 + x3 + x6 >= 32',
        'x1 + x3 + x5 + x6 >= 24',
        'x1 + x3 + x7 >= 24',
        'x1 + x2 + x4 >= 24',
        'x3 + x5 + x7 >= 24',
        'x1 + x6 + x7 >= 24',
        'x2 + x3 + x4 >= 24',
        'x1 + x2 + x6 >= 24',
        'x1 + x4 + x6 >= 24',
        'x1 + x4 + x5 >= 24',
        'x4 + x6 + x7 >= 24',
        'x4 + x5 + x6 >= 24',
        'x1 + x2 + x5 >= 24',
        'x5 + x6 + x7 >= 24',
        'x2 + x4 + x5 >= 24',
        'x1 + x3 + x4 >= 24',
        'x2 + x3 + x7 >= 24',
        'x1 + x5 + x6 >= 24',
        'x2 + x6 + x7 >= 24',
        'x4 + x5 + x7 >= 24',
        'x1 + x3 + x6 >= 27',
        'x1 + x3 + x7 >= 27',
        'x1 + x2 + x4 >= 27',
        'x3 + x5 + x7 >= 27',
        'x1 + x6 + x7 >= 27',
        'x2 + x3 + x4 >= 27',
        'x1 + x2 + x6 >= 27',
        'x1 + x4 + x6 >= 27',
        'x1 + x4 + x5 >= 27',
        'x4 + x6 + x7 >= 27',
        'x4 + x5 + x6 >= 27',
        'x1 + x2 + x5 >= 27',
        'x5 + x6 + x7 >= 27',
        'x2 + x4 + x5 >= 27',
        'x1 + x3 + x4 >= 27',
        'x2 + x3 + x7 >= 27',
        'x1 + x5 + x6 >= 27',
        'x2 + x6 + x7 >= 27',
        'x4 + x5 + x7 >= 27',
        'x1 + x3 + x6 >= 29',
        'x1 + x3 + x7 >= 29',
        'x1 + x2 + x4 >= 29',
        'x3 + x5 + x7 >= 29',
        'x1 + x6 + x7 >= 29',
        'x2 + x3 + x4 >= 29',
        'x1 + x2 + x6 >= 29',
        'x1 + x4 + x6 >= 29',
        'x1 + x4 + x5 >= 29',
        'x4 + x6 + x7 >= 29',
        'x4 + x5 + x6 >= 29',
        'x1 + x2 + x5 >= 29',
        'x5 + x6 + x7 >= 29',
        'x2 + x4 + x5 >= 29',
        'x1 + x3 + x4 >= 29',
        'x2 + x3 + x7 >= 29',
        'x1 + x5 + x6 >= 29',
        'x2 + x6 + x7 >= 29',
        'x4 + x5 + x7 >= 29',
        'x1 + x3 + x6 >= 33',
        'x1 + x3 + x7 >= 33',
        'x1 + x2 + x4 >= 33',
        'x3 + x5 + x7 >= 33',
        'x1 + x6 + x7 >= 33',
        'x2 + x3 + x4 >= 33',
        'x1 + x2 + x6 >= 33',
        'x1 + x4 + x6 >= 33',
        'x1 + x4 + x5 >= 33',
        'x4 + x6 + x7 >= 33',
        'x4 + x5 + x6 >= 33',
        'x1 + x2 + x5 >= 33',
        'x5 + x6 + x7 >= 33',
        'x2 + x4 + x5 >= 33',
        'x1 + x3 + x4 >= 33',
        'x2 + x3 + x7 >= 33',
        'x1 + x5 + x6 >= 33',
        'x2 + x6 + x7 >= 33',
        'x4 + x5 + x7 >= 33',
        'x1 + x3 + x6 >= 40',
        'x1 + x3 + x7 >= 40',
        'x1 + x2 + x4 >= 40',
        'x3 + x5 + x7 >= 40',
        'x1 + x6 + x7 >= 40',
        'x2 + x3 + x4 >= 40',
        'x1 + x2 + x6 >= 40',
        'x1 + x4 + x6 >= 40',
        'x1 + x4 + x5 >= 40',
        'x4 + x6 + x7 >= 40',
        'x4 + x5 + x6 >= 40',
        'x1 + x2 + x5 >= 40',
        'x5 + x6 + x7 >= 40',
        'x2 + x4 + x5 >= 40',
        'x1 + x3 + x4 >= 40',
        'x2 + x3 + x7 >= 40',
        'x1 + x5 + x6 >= 40',
        'x2 + x6 + x7 >= 40',
        'x4 + x5 + x7 >= 40',
        'x1*x1 == x1', 
        'x2*x2 == x2', 
        'x3*x3 == x3', 
        'x4*x4 == x4', 
        'x5*x5 == x5', 
        'x6*x6 == x6', 
        'x7*x7 == x7'
    ]
}
```

Now let's create a python code using Gurobi to solve this optimization problem.

```python
import gurobi

def solve_optimization_problem():
    model = gurobi.Model()

    # Define variables
    x1 = model.addVar(name="cantaloupes", vtype=gurobi.GRB.INTEGER)
    x2 = model.addVar(name="chicken drumsticks", vtype=gurobi.GRB.INTEGER)
    x3 = model.addVar(name="tomatoes", vtype=gurobi.GRB.INTEGER)
    x4 = model.addVar(name="bowls of cereal", vtype=gurobi.GRB.INTEGER)
    x5 = model.addVar(name="bowls of pasta", vtype=gurobi.GRB.INTEGER)
    x6 = model.addVar(name="bowls of instant ramen", vtype=gurobi.GRB.INTEGER)
    x7 = model.addVar(name="corn cobs", vtype=gurobi.GRB.INTEGER)

    # Objective function
    model.setObjective(5*x1 + 2*x2 + 8*x3 + 9*x4 + 9*x5 + 1*x6 + 2*x7, gurobi.GRB.MINIMIZE)

    # Constraints
    model.addConstr(7*x1 + 9*x2 + 6*x3 + 10*x4 + 10*x5 + 9*x6 + 11*x7 <= 304)
    model.addConstr(x4 + x7 >= 32)
    model.addConstr(x4 + x5 >= 15)
    model.addConstr(x3 + x7 >= 24)
    model.addConstr(x5 + x7 >= 26)
    model.addConstr(x4 + x6 >= 28)
    model.addConstr(x3 + x5 >= 15)
    model.addConstr(x1 + x3 >= 23)
    model.addConstr(x5 + x6 >= 24)
    model.addConstr(x1 + x5 >= 32)
    model.addConstr(x1 + x2 >= 40)
    model.addConstr(x3 + x5 + x6 >= 32)
    model.addConstr(x1 + x3 + x7 >= 32)
    model.addConstr(x1 + x2 + x4 >= 32)
    model.addConstr(x3 + x5 + x7 >= 32)
    model.addConstr(x1 + x6 + x7 >= 32)
    model.addConstr(x2 + x3 + x4 >= 32)
    model.addConstr(x1 + x2 + x6 >= 32)
    model.addConstr(x1 + x4 + x6 >= 32)
    model.addConstr(x1 + x4 + x5 >= 32)
    model.addConstr(x4 + x6 + x7 >= 32)
    model.addConstr(x4 + x5 + x6 >= 32)
    model.addConstr(x1 + x2 + x5 >= 32)
    model.addConstr(x5 + x6 + x7 >= 32)
    model.addConstr(x2 + x4 + x5 >= 32)

    # Solve the model
    model.optimize()

    if model.status == gurobi.GRB.OPTIMAL:
        print("Objective: ", model.objval)
        print("cantaloupes: ", x1.varValue)
        print("chicken drumsticks: ", x2.varValue)
        print("tomatoes: ", x3.varValue)
        print("bowls of cereal: ", x4.varValue)
        print("bowls of pasta: ", x5.varValue)
        print("bowls of instant ramen: ", x6.varValue)
        print("corn cobs: ", x7.varValue)
    else:
        print("No solution found")

solve_optimization_problem()
```