## Step 1: Define the symbolic representation of the variables
The variables are 'bowls of cereal', 'knishes', 'peanutbutter sandwiches', and 'sashimi', which can be represented symbolically as $x_0, x_1, x_2, x_3$ respectively.

## Step 2: Convert the objective function into a symbolic representation
The objective function to minimize is $9.04x_0 + 6.21x_1 + 6.36x_2 + 3.02x_3$.

## Step 3: List the constraints in symbolic notation
The constraints are:
1. $13x_0 + 10x_2 + 4x_3 \geq 15$ (total combined umami index from bowls of cereal, and peanutbutter sandwiches)
2. $13x_0 + 3x_1 \geq 8$ (total combined umami index from bowls of cereal plus knishes)
3. $13x_0 + 4x_3 \geq 19$ (total combined umami index from bowls of cereal, and sashimi)
4. $13x_0 + 3x_1 + 10x_2 + 4x_3 \geq 19$ (total combined umami index from all)
5. $12x_0 + 7x_1 \geq 20$ (at least 20 grams of carbohydrates from bowls of cereal, and knishes)
6. $12x_0 + 12x_3 \geq 15$ (at least 15 grams of carbohydrates from bowls of cereal, and sashimi)
7. $12x_0 + 7x_1 + 11x_2 + 12x_3 \geq 15$ (at least 15 grams of carbohydrates from all)
8. $3x_0 - x_2 \geq 0$ (3 times the number of bowls of cereal, plus minus one times the number of peanutbutter sandwiches)
9. $3x_1 + 10x_2 \leq 53$ (total combined umami index from knishes and peanutbutter sandwiches)
10. $10x_2 + 4x_3 \leq 46$ (total combined umami index from peanutbutter sandwiches plus sashimi)
11. $3x_1 + 4x_3 \leq 32$ (total combined umami index from knishes, and sashimi)
12. $7x_1 + 12x_3 \leq 69$ (no more than 69 grams of carbohydrates from knishes plus sashimi)
13. $7x_1 + 11x_2 + 12x_3 \leq 66$ (no more than 66 grams of carbohydrates from knishes plus peanutbutter sandwiches plus sashimi)
14. $12x_0 + 7x_1 + 12x_3 \leq 35$ (no more than 35 grams of carbohydrates from bowls of cereal, knishes and sashimi)
15. $12x_0 + 7x_1 + 11x_2 \leq 46$ (no more than 46 grams of carbohydrates from bowls of cereal plus knishes plus peanutbutter sandwiches)
16. $12x_0 + 11x_2 + 12x_3 \leq 48$ (no more than 48 grams of carbohydrates from bowls of cereal, peanutbutter sandwiches and sashimi)

## Step 4: Define the symbolic representation of the problem
```json
{
    'sym_variables': [
        ('x0', 'bowls of cereal'), 
        ('x1', 'knishes'), 
        ('x2', 'peanutbutter sandwiches'), 
        ('x3', 'sashimi')
    ], 
    'objective_function': '9.04*x0 + 6.21*x1 + 6.36*x2 + 3.02*x3', 
    'constraints': [
        '13*x0 + 10*x2 + 4*x3 >= 15',
        '13*x0 + 3*x1 >= 8',
        '13*x0 + 4*x3 >= 19',
        '13*x0 + 3*x1 + 10*x2 + 4*x3 >= 19',
        '12*x0 + 7*x1 >= 20',
        '12*x0 + 12*x3 >= 15',
        '12*x0 + 7*x1 + 11*x2 + 12*x3 >= 15',
        '3*x0 - x2 >= 0',
        '3*x1 + 10*x2 <= 53',
        '10*x2 + 4*x3 <= 46',
        '3*x1 + 4*x3 <= 32',
        '7*x1 + 12*x3 <= 69',
        '7*x1 + 11*x2 + 12*x3 <= 66',
        '12*x0 + 7*x1 + 12*x3 <= 35',
        '12*x0 + 7*x1 + 11*x2 <= 46',
        '12*x0 + 11*x2 + 12*x3 <= 48'
    ]
}
```

## Step 5: Write the Gurobi code to solve the optimization problem
```python
import gurobi

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

    # Define the variables
    x0 = model.addVar(name="bowls_of_cereal", lb=0)
    x1 = model.addVar(name="knishes", lb=0)
    x2 = model.addVar(name="peanutbutter_sandwiches", lb=0)
    x3 = model.addVar(name="sashimi", lb=0)

    # Define the objective function
    model.setObjective(9.04 * x0 + 6.21 * x1 + 6.36 * x2 + 3.02 * x3, gurobi.GRB.MINIMIZE)

    # Add constraints
    model.addConstr(13 * x0 + 10 * x2 + 4 * x3 >= 15)
    model.addConstr(13 * x0 + 3 * x1 >= 8)
    model.addConstr(13 * x0 + 4 * x3 >= 19)
    model.addConstr(13 * x0 + 3 * x1 + 10 * x2 + 4 * x3 >= 19)
    model.addConstr(12 * x0 + 7 * x1 >= 20)
    model.addConstr(12 * x0 + 12 * x3 >= 15)
    model.addConstr(12 * x0 + 7 * x1 + 11 * x2 + 12 * x3 >= 15)
    model.addConstr(3 * x0 - x2 >= 0)
    model.addConstr(3 * x1 + 10 * x2 <= 53)
    model.addConstr(10 * x2 + 4 * x3 <= 46)
    model.addConstr(3 * x1 + 4 * x3 <= 32)
    model.addConstr(7 * x1 + 12 * x3 <= 69)
    model.addConstr(7 * x1 + 11 * x2 + 12 * x3 <= 66)
    model.addConstr(12 * x0 + 7 * x1 + 12 * x3 <= 35)
    model.addConstr(12 * x0 + 7 * x1 + 11 * x2 <= 46)
    model.addConstr(12 * x0 + 11 * x2 + 12 * x3 <= 48)

    # Optimize the model
    model.optimize()

    # Print the solution
    if model.status == gurobi.GRB.OPTIMAL:
        print("Objective: ", model.objVal)
        print("bowls_of_cereal: ", x0.varValue)
        print("knishes: ", x1.varValue)
        print("peanutbutter_sandwiches: ", x2.varValue)
        print("sashimi: ", x3.varValue)
    else:
        print("The model is infeasible")

solve_optimization_problem()
```