## Step 1: Define the symbolic representation of the problem
The problem involves variables: cornichons, strawberries, cantaloupes, and bowls of pasta, which we can denote as $x_0, x_1, x_2, x_3$ respectively.

## Step 2: Translate the objective function into symbolic notation
The objective function to minimize is $5.5x_0 + 6.03x_1 + 7.82x_2 + 6.25x_3$.

## 3: List the constraints in symbolic notation
1. $6x_0 + x_1 + 11x_2 + 14x_3 \leq 92$ (fiber constraint)
2. $14x_0 + 4x_1 + 10x_2 + x_3 \leq 223$ (carbohydrates constraint)
3. $x_1 + 11x_2 \geq 20$ (fiber from strawberries and cantaloupes)
4. $11x_2 + 14x_3 \geq 14$ (fiber from cantaloupes and bowls of pasta)
5. $6x_0 + x_1 + 11x_2 + 14x_3 \geq 14$ (fiber from all sources)
6. $14x_0 + 4x_1 \geq 23$ (carbohydrates from cornichons and strawberries)
7. $10x_2 + x_3 \geq 55$ (carbohydrates from cantaloupes and bowls of pasta)
8. $14x_0 + 10x_2 \geq 55$ (carbohydrates from cornichons and cantaloupes)
9. $14x_0 + 4x_1 + x_3 \geq 37$ (carbohydrates from cornichons, strawberries, and bowls of pasta)
10. $14x_0 + 4x_1 + 10x_2 + x_3 \geq 37$ (carbohydrates from all sources)
11. $-x_1 + x_2 \geq 0$ (relationship between strawberries and cantaloupes)
12. $4x_0 - 6x_3 \geq 0$ (relationship between cornichons and bowls of pasta)
13. $6x_0 + x_1 \leq 61$ (fiber from cornichons and strawberries)
14. $x_1 + 11x_2 \leq 36$ (fiber from strawberries and cantaloupes)
15. $6x_0 + 11x_2 \leq 70$ (fiber from cornichons and cantaloupes)
16. $11x_2 + 14x_3 \leq 91$ (fiber from cantaloupes and bowls of pasta)
17. $14x_0 + 10x_2 \leq 72$ (carbohydrates from cornichons and cantaloupes)

## 4: Provide the symbolic representation in the required format
```json
{
    'sym_variables': [('x0', 'cornichons'), ('x1', 'strawberries'), ('x2', 'cantaloupes'), ('x3', 'bowls of pasta')],
    'objective_function': '5.5*x0 + 6.03*x1 + 7.82*x2 + 6.25*x3',
    'constraints': [
        '6*x0 + x1 + 11*x2 + 14*x3 <= 92',
        '14*x0 + 4*x1 + 10*x2 + x3 <= 223',
        'x1 + 11*x2 >= 20',
        '11*x2 + 14*x3 >= 14',
        '6*x0 + x1 + 11*x2 + 14*x3 >= 14',
        '14*x0 + 4*x1 >= 23',
        '10*x2 + x3 >= 55',
        '14*x0 + 10*x2 >= 55',
        '14*x0 + 4*x1 + x3 >= 37',
        '14*x0 + 4*x1 + 10*x2 + x3 >= 37',
        '-x1 + x2 >= 0',
        '4*x0 - 6*x3 >= 0',
        '6*x0 + x1 <= 61',
        'x1 + 11*x2 <= 36',
        '6*x0 + 11*x2 <= 70',
        '11*x2 + 14*x3 <= 91',
        '14*x0 + 10*x2 <= 72'
    ]
}
```

## 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="cornichons", lb=-gurobi.GRB.INFINITY, ub=gurobi.GRB.INFINITY)
    x1 = model.addVar(name="strawberries", lb=-gurobi.GRB.INFINITY, ub=gurobi.GRB.INFINITY)
    x2 = model.addVar(name="cantaloupes", lb=-gurobi.GRB.INFINITY, ub=gurobi.GRB.INFINITY)
    x3 = model.addVar(name="bowls of pasta", lb=-gurobi.GRB.INFINITY, ub=gurobi.GRB.INFINITY)

    # Define the objective function
    model.setObjective(5.5*x0 + 6.03*x1 + 7.82*x2 + 6.25*x3, gurobi.GRB.MINIMIZE)

    # Add constraints
    model.addConstr(6*x0 + x1 + 11*x2 + 14*x3 <= 92)
    model.addConstr(14*x0 + 4*x1 + 10*x2 + x3 <= 223)
    model.addConstr(x1 + 11*x2 >= 20)
    model.addConstr(11*x2 + 14*x3 >= 14)
    model.addConstr(6*x0 + x1 + 11*x2 + 14*x3 >= 14)
    model.addConstr(14*x0 + 4*x1 >= 23)
    model.addConstr(10*x2 + x3 >= 55)
    model.addConstr(14*x0 + 10*x2 >= 55)
    model.addConstr(14*x0 + 4*x1 + x3 >= 37)
    model.addConstr(14*x0 + 4*x1 + 10*x2 + x3 >= 37)
    model.addConstr(-x1 + x2 >= 0)
    model.addConstr(4*x0 - 6*x3 >= 0)
    model.addConstr(6*x0 + x1 <= 61)
    model.addConstr(x1 + 11*x2 <= 36)
    model.addConstr(6*x0 + 11*x2 <= 70)
    model.addConstr(11*x2 + 14*x3 <= 91)
    model.addConstr(14*x0 + 10*x2 <= 72)

    # Optimize the model
    model.optimize()

    # Print the solution
    if model.status == gurobi.GRB.OPTIMAL:
        print("Optimal solution found.")
        print("Objective: ", model.objval)
        print("cornichons: ", x0.x)
        print("strawberries: ", x1.x)
        print("cantaloupes: ", x2.x)
        print("bowls of pasta: ", x3.x)
    else:
        print("No optimal solution found.")

optimize_problem()
```