## Step 1: Define the symbolic representation of the problem
The problem involves three variables: 'bagged salads', 'tomatoes', and 'cornichons', which can be represented symbolically as $x_0$, $x_1$, and $x_2$ respectively.

## Step 2: Translate the objective function into symbolic notation
The objective function to minimize is $6x_0 + 6x_1 + 3x_2$.

## Step 3: Define the constraints in symbolic notation
The constraints given are:
- $8x_0 + 20x_1 + 3x_2 \geq 59$ (total healthiness rating from bagged salads and cornichons is not correctly represented, it should be from bagged salads and tomatoes, and cornichons separately),
- $20x_1 + 3x_2 \geq 56$ (healthiness from tomatoes and cornichons),
- $8x_0 + 20x_1 + 3x_2 \geq 56$ (total healthiness),
- $8x_0 + 20x_1 + 3x_2 \geq 56$ (same as above, redundant),
- $4x_0 + 4x_1 \geq 58$ (fiber from bagged salads and tomatoes),
- $4x_0 + 4x_2 \geq 87$ (fiber from bagged salads and cornichons),
- $4x_1 + 4x_2 \geq 33$ (fiber from tomatoes and cornichons),
- $4x_0 + 4x_1 + 4x_2 \geq 33$ (total fiber, redundant with others),
- $-6x_1 + 4x_2 \geq 0$,
- $-6x_0 + 5x_2 \geq 0$,
- $8x_0 + 20x_1 + 3x_2 \leq 184$ (total healthiness rating upper bound),
- $4x_0 + 4x_1 \leq 155$ (fiber upper bound from bagged salads and tomatoes),
- $4x_1 + 4x_2 \leq 107$ (fiber upper bound from tomatoes and cornichons),
- $4x_0 + 4x_1 + 4x_2 \leq 178$ (total fiber upper bound).

## 4: Correct and simplify constraints
Correcting and simplifying:
- The healthiness constraints should reflect that bagged salads, tomatoes, and cornichons each contribute to the total healthiness rating.
- The actual constraints based on the problem description are:
  - $8x_0 + 3x_2 \geq 59$,
  - $20x_1 + 3x_2 \geq 56$,
  - $8x_0 + 20x_1 + 3x_2 \geq 56$,
  - $4x_0 + 4x_1 \geq 58$,
  - $4x_0 + 4x_2 \geq 87$,
  - $4x_1 + 4x_2 \geq 33$,
  - $4(x_0 + x_1 + x_2) \geq 33$,
  - $-6x_1 + 4x_2 \geq 0$,
  - $-6x_0 + 5x_2 \geq 0$,
  - $8x_0 + 20x_1 + 3x_2 \leq 184$,
  - $4x_0 + 4x_1 \leq 155$,
  - $4x_1 + 4x_2 \leq 107$,
  - $4(x_0 + x_1 + x_2) \leq 178$.

## 5: Formulate the problem in Gurobi
We will use Gurobi to solve this linear programming problem.

## 6: Write the Gurobi code
```python
import gurobi

# Create a new model
m = gurobi.Model()

# Define the variables
x0 = m.addVar(name="bagged_salads", lb=0)
x1 = m.addVar(name="tomatoes", lb=0)
x2 = m.addVar(name="cornichons", lb=0)

# Objective function
m.setObjective(6*x0 + 6*x1 + 3*x2, gurobi.GRB.MINIMIZE)

# Constraints
m.addConstr(8*x0 + 3*x2 >= 59)
m.addConstr(20*x1 + 3*x2 >= 56)
m.addConstr(8*x0 + 20*x1 + 3*x2 >= 56)
m.addConstr(4*x0 + 4*x1 >= 58)
m.addConstr(4*x0 + 4*x2 >= 87)
m.addConstr(4*x1 + 4*x2 >= 33)
m.addConstr(4*x0 + 4*x1 + 4*x2 >= 33)
m.addConstr(-6*x1 + 4*x2 >= 0)
m.addConstr(-6*x0 + 5*x2 >= 0)
m.addConstr(8*x0 + 20*x1 + 3*x2 <= 184)
m.addConstr(4*x0 + 4*x1 <= 155)
m.addConstr(4*x1 + 4*x2 <= 107)
m.addConstr(4*x0 + 4*x1 + 4*x2 <= 178)

# Optimize the model
m.optimize()

# Print the solution
if m.status == gurobi.GRB.OPTIMAL:
    print("Objective: ", m.objVal)
    print("bagged_salads: ", x0.varValue)
    print("tomatoes: ", x1.varValue)
    print("cornichons: ", x2.varValue)
else:
    print("The model is infeasible")
```

## 7: Symbolic representation
```json
{
    'sym_variables': [('x0', 'bagged salads'), ('x1', 'tomatoes'), ('x2', 'cornichons')],
    'objective_function': '6*x0 + 6*x1 + 3*x2',
    'constraints': [
        '8*x0 + 3*x2 >= 59',
        '20*x1 + 3*x2 >= 56',
        '8*x0 + 20*x1 + 3*x2 >= 56',
        '4*x0 + 4*x1 >= 58',
        '4*x0 + 4*x2 >= 87',
        '4*x1 + 4*x2 >= 33',
        '4*x0 + 4*x1 + 4*x2 >= 33',
        '-6*x1 + 4*x2 >= 0',
        '-6*x0 + 5*x2 >= 0',
        '8*x0 + 20*x1 + 3*x2 <= 184',
        '4*x0 + 4*x1 <= 155',
        '4*x1 + 4*x2 <= 107',
        '4*x0 + 4*x1 + 4*x2 <= 178'
    ]
}
```