## Step 1: Define the symbolic representation of the variables
The variables are 'apples', 'rotisserie chickens', and 'protein bars', which we will denote as $x_0$, $x_1$, and $x_2$ respectively.

## Step 2: Define the objective function in symbolic notation
The objective function to maximize is $6x_0 + 6x_1 + 8x_2$.

## Step 3: Define the constraints in symbolic notation
The constraints are:
- $5x_1 + 8x_2 \geq 15$ (tastiness rating from rotisserie chickens and protein bars)
- $2x_0 + 8x_1 \geq 24$ (grams of protein from apples and rotisserie chickens)
- $8x_1 + 5x_2 \geq 23$ (grams of protein from rotisserie chickens and protein bars)
- $2x_0 + 2x_2 \geq 26$ (spend at least $26 on apples and protein bars)
- $2x_0 + 4x_1 + 2x_2 \geq 28$ (spend at least $28 on apples, rotisserie chickens, and protein bars)
- $2x_0 + x_2 \geq 8$ (grams of carbohydrates from apples and protein bars)
- $5x_1 + 8x_2 \leq 20$ (tastiness rating from rotisserie chickens and protein bars)
- $6x_0 + 5x_1 \leq 51$ (tastiness rating from apples and rotisserie chickens)
- $6x_0 + 5x_1 + 8x_2 \leq 51$ (tastiness rating from apples, rotisserie chickens, and protein bars)
- $2x_0 + 5x_2 \leq 56$ (grams of protein from apples and protein bars)
- $2x_0 + 8x_1 + 5x_2 \leq 56$ (grams of protein from apples, rotisserie chickens, and protein bars)
- $3x_1 + 4x_2 \leq 43$ (healthiness rating from rotisserie chickens and protein bars)
- $7x_0 + 3x_1 \leq 88$ (healthiness rating from apples and rotisserie chickens)
- $7x_0 + 3x_1 + 4x_2 \leq 88$ (healthiness rating from apples, rotisserie chickens, and protein bars)
- $2x_0 + 4x_1 \leq 47$ (spend at most $47 on apples and rotisserie chickens)
- $2x_0 + 4x_1 + 2x_2 \leq 47$ (spend at most $47 on apples, rotisserie chickens, and protein bars)
- $5x_1 + x_2 \leq 44$ (grams of carbohydrates from rotisserie chickens and protein bars)
- $2x_0 + x_2 \leq 51$ (grams of carbohydrates from apples and protein bars)
- $2x_0 + 5x_1 \leq 25$ (grams of carbohydrates from apples and rotisserie chickens)
- $2x_0 + 5x_1 + x_2 \leq 25$ (grams of carbohydrates from apples, rotisserie chickens, and protein bars)
- $x_0 \geq 0$ and $x_0$ is an integer (apples)
- $x_1 \geq 0$ and $x_1$ is an integer (rotisserie chickens)
- $x_2 \geq 0$ (protein bars)

## Step 4: Provide the symbolic representation of the problem
```json
{
    'sym_variables': [('x0', 'apples'), ('x1', 'rotisserie chickens'), ('x2', 'protein bars')],
    'objective_function': '6*x0 + 6*x1 + 8*x2',
    'constraints': [
        '5*x1 + 8*x2 >= 15',
        '2*x0 + 8*x1 >= 24',
        '8*x1 + 5*x2 >= 23',
        '2*x0 + 2*x2 >= 26',
        '2*x0 + 4*x1 + 2*x2 >= 28',
        '2*x0 + x2 >= 8',
        '5*x1 + 8*x2 <= 20',
        '6*x0 + 5*x1 <= 51',
        '6*x0 + 5*x1 + 8*x2 <= 51',
        '2*x0 + 5*x2 <= 56',
        '2*x0 + 8*x1 + 5*x2 <= 56',
        '3*x1 + 4*x2 <= 43',
        '7*x0 + 3*x1 <= 88',
        '7*x0 + 3*x1 + 4*x2 <= 88',
        '2*x0 + 4*x1 <= 47',
        '2*x0 + 4*x1 + 2*x2 <= 47',
        '5*x1 + x2 <= 44',
        '2*x0 + x2 <= 51',
        '2*x0 + 5*x1 <= 25',
        '2*x0 + 5*x1 + x2 <= 25',
        'x0 >= 0', 'x0 == int(x0)',
        'x1 >= 0', 'x1 == int(x1)',
        'x2 >= 0'
    ]
}
```

## Step 5: Write the Gurobi code
```python
import gurobi

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

    # Define the variables
    x0 = model.addVar(name="apples", vtype=gurobi.GRB.INTEGER)
    x1 = model.addVar(name="rotisserie_chickens", vtype=gurobi.GRB.INTEGER)
    x2 = model.addVar(name="protein_bars")

    # Define the objective function
    model.setObjective(6 * x0 + 6 * x1 + 8 * x2, gurobi.GRB.MAXIMIZE)

    # Add constraints
    model.addConstr(5 * x1 + 8 * x2 >= 15)
    model.addConstr(2 * x0 + 8 * x1 >= 24)
    model.addConstr(8 * x1 + 5 * x2 >= 23)
    model.addConstr(2 * x0 + 2 * x2 >= 26)
    model.addConstr(2 * x0 + 4 * x1 + 2 * x2 >= 28)
    model.addConstr(2 * x0 + x2 >= 8)
    model.addConstr(5 * x1 + 8 * x2 <= 20)
    model.addConstr(6 * x0 + 5 * x1 <= 51)
    model.addConstr(6 * x0 + 5 * x1 + 8 * x2 <= 51)
    model.addConstr(2 * x0 + 5 * x2 <= 56)
    model.addConstr(2 * x0 + 8 * x1 + 5 * x2 <= 56)
    model.addConstr(3 * x1 + 4 * x2 <= 43)
    model.addConstr(7 * x0 + 3 * x1 <= 88)
    model.addConstr(7 * x0 + 3 * x1 + 4 * x2 <= 88)
    model.addConstr(2 * x0 + 4 * x1 <= 47)
    model.addConstr(2 * x0 + 4 * x1 + 2 * x2 <= 47)
    model.addConstr(5 * x1 + x2 <= 44)
    model.addConstr(2 * x0 + x2 <= 51)
    model.addConstr(2 * x0 + 5 * x1 <= 25)
    model.addConstr(2 * x0 + 5 * x1 + x2 <= 25)

    # Set bounds for variables
    x0.lb = 0
    x1.lb = 0
    x2.lb = 0

    # Optimize the model
    model.optimize()

    # Print the solution
    if model.status == gurobi.GRB.OPTIMAL:
        print("Objective: ", model.objval)
        print("Apples: ", x0.varValue)
        print("Rotisserie Chickens: ", x1.varValue)
        print("Protein Bars: ", x2.varValue)
    else:
        print("The model is infeasible")

solve_optimization_problem()
```