## Step 1: Define the symbolic representation of the problem
First, let's define the symbolic variables and their corresponding natural language objects:
- $x_0$ = oreos
- $x_1$ = protein bars
- $x_2$ = bowls of instant ramen
- $x_3$ = tomatoes

## Step 2: Formulate the objective function
The objective function to minimize is $2x_0 + 6x_1 + 6x_2 + x_3$.

## Step 3: List all constraints
### Resource constraints
- Healthiness rating constraint for oreos: $7x_0 \leq 217$
- Healthiness rating constraint for protein bars: $11x_1 \leq 217$
- Healthiness rating constraint for bowls of instant ramen: $6x_2 \leq 217$
- Healthiness rating constraint for tomatoes: $1x_3 \leq 217$
- Carbohydrates constraint for oreos: $4x_0 \leq 125$
- Carbohydrates constraint for protein bars: $25x_1 \leq 125$
- Carbohydrates constraint for bowls of instant ramen: $26x_2 \leq 125$
- Carbohydrates constraint for tomatoes: $29x_3 \leq 125$

### Minimum combined healthiness rating constraints
- $7x_0 + x_3 \geq 53$
- $7x_0 + 6x_2 \geq 43$
- $7x_0 + 11x_1 \geq 47$
- $11x_1 + x_3 \geq 52$
- $7x_0 + 11x_1 + 6x_2 + x_3 \geq 52$

### Minimum carbohydrates constraints
- $4x_0 + 25x_1 \geq 18$
- $4x_0 + 25x_1 + 26x_2 + 29x_3 \geq 18$

### Maximum combined healthiness rating constraints
- $7x_0 + 6x_2 \leq 168$
- $7x_0 + x_3 \leq 109$

### Maximum carbohydrates constraints
- $4x_0 + 26x_2 + 29x_3 \leq 86$
- $4x_0 + 25x_1 + 26x_2 \leq 48$

## Step 4: Provide the symbolic representation of the problem
```json
{
    'sym_variables': [
        ('x0', 'oreos'),
        ('x1', 'protein bars'),
        ('x2', 'bowls of instant ramen'),
        ('x3', 'tomatoes')
    ],
    'objective_function': '2*x0 + 6*x1 + 6*x2 + x3',
    'constraints': [
        '7*x0 <= 217',
        '11*x1 <= 217',
        '6*x2 <= 217',
        'x3 <= 217',
        '4*x0 <= 125',
        '25*x1 <= 125',
        '26*x2 <= 125',
        '29*x3 <= 125',
        '7*x0 + x3 >= 53',
        '7*x0 + 6*x2 >= 43',
        '7*x0 + 11*x1 >= 47',
        '11*x1 + x3 >= 52',
        '7*x0 + 11*x1 + 6*x2 + x3 >= 52',
        '4*x0 + 25*x1 >= 18',
        '4*x0 + 25*x1 + 26*x2 + 29*x3 >= 18',
        '7*x0 + 6*x2 <= 168',
        '7*x0 + x3 <= 109',
        '4*x0 + 26*x2 + 29*x3 <= 86',
        '4*x0 + 25*x1 + 26*x2 <= 48'
    ]
}
```

## Step 5: Implement the optimization problem using Gurobi
```python
import gurobi

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

    # Define the variables
    x0 = model.addVar(name="x0", lb=0)  # oreos
    x1 = model.addVar(name="x1", lb=0)  # protein bars
    x2 = model.addVar(name="x2", lb=0)  # bowls of instant ramen
    x3 = model.addVar(name="x3", lb=0)  # tomatoes

    # Objective function
    model.setObjective(2*x0 + 6*x1 + 6*x2 + x3, gurobi.GRB.MINIMIZE)

    # Constraints
    model.addConstr(7*x0 <= 217)
    model.addConstr(11*x1 <= 217)
    model.addConstr(6*x2 <= 217)
    model.addConstr(x3 <= 217)
    model.addConstr(4*x0 <= 125)
    model.addConstr(25*x1 <= 125)
    model.addConstr(26*x2 <= 125)
    model.addConstr(29*x3 <= 125)

    model.addConstr(7*x0 + x3 >= 53)
    model.addConstr(7*x0 + 6*x2 >= 43)
    model.addConstr(7*x0 + 11*x1 >= 47)
    model.addConstr(11*x1 + x3 >= 52)
    model.addConstr(7*x0 + 11*x1 + 6*x2 + x3 >= 52)
    model.addConstr(4*x0 + 25*x1 >= 18)
    model.addConstr(4*x0 + 25*x1 + 26*x2 + 29*x3 >= 18)
    model.addConstr(7*x0 + 6*x2 <= 168)
    model.addConstr(7*x0 + x3 <= 109)
    model.addConstr(4*x0 + 26*x2 + 29*x3 <= 86)
    model.addConstr(4*x0 + 25*x1 + 26*x2 <= 48)

    # Optimize the model
    model.optimize()

    # Print the solution
    if model.status == gurobi.GRB.OPTIMAL:
        print("Objective: ", model.objval)
        print("Oreos: ", x0.varValue)
        print("Protein bars: ", x1.varValue)
        print("Bowls of instant ramen: ", x2.varValue)
        print("Tomatoes: ", x3.varValue)
    else:
        print("The model is infeasible")

optimize_problem()
```