## Step 1: Define the symbolic representation of the variables
The variables are ['milligrams of zinc', 'milligrams of vitamin B1', 'grams of carbohydrates', 'grams of protein'] which can be represented symbolically as $x_0, x_1, x_2, x_3$ respectively.

## Step 2: Convert the natural language objects into symbolic notation
The symbolic representation of the variables is:
- $x_0$ : milligrams of zinc
- $x_1$ : milligrams of vitamin B1
- $x_2$ : grams of carbohydrates
- $x_3$ : grams of protein

## Step 3: Define the objective function in symbolic notation
The objective function to maximize is $3x_0 + 3x_1 + 5x_2 + 6x_3$.

## Step 4: List the constraints in symbolic notation
The constraints are:
- $x_0 \geq 0$
- $x_1 \geq 0$
- $x_2 \geq 0$
- $x_3 \geq 0$
- $1x_0 + 4x_1 + 7x_2 + 17x_3 \geq 41$
- $1x_1 + 4x_0 + 7x_2 + 17x_3 \geq 41$ (Corrected for accurate representation)
- $1x_0 + 4x_1 + 17x_3 \geq 41$
- $1x_0 + 7x_2 + 17x_3 \geq 62$
- $4x_1 + 7x_2 + 17x_3 \geq 62$
- $12x_0 + 6x_1 + 17x_3 \geq 62$
- $12x_0 + 15x_2 + 17x_3 \geq 62$
- $4x_1 + 15x_2 + 17x_3 \geq 62$
- $12x_0 + 6x_1 + 17x_3 \geq 62$
- $12x_0 + 15x_2 \geq 79$
- $12x_0 + 17x_3 \geq 54$
- $15x_2 + 17x_3 \geq 59$
- $12x_0 + 6x_1 \geq 72$
- $4x_1 + 7x_2 \leq 263$
- $1x_0 + 17x_3 \leq 90$
- $4x_1 + 17x_3 \leq 118$
- $1x_0 + 7x_2 \leq 127$
- $1x_0 + 4x_1 \leq 133$
- $1x_0 + 4x_1 + 17x_3 \leq 210$
- $1x_0 + 7x_2 + 17x_3 \leq 261$
- $1x_0 + 4x_1 + 7x_2 \leq 130$
- $1x_0 + 4x_1 + 7x_2 + 17x_3 \leq 130$
- $12x_0 + 17x_3 \leq 229$
- $12x_0 + 6x_1 \leq 259$
- $6x_1 + 15x_2 \leq 254$
- $12x_0 + 15x_2 \leq 225$
- $15x_2 + 17x_3 \leq 208$
- $12x_0 + 6x_1 + 15x_2 + 17x_3 \leq 208$

## 5: Provide the symbolic representation of the problem
```json
{
'sym_variables': [
    ('x0', 'milligrams of zinc'), 
    ('x1', 'milligrams of vitamin B1'), 
    ('x2', 'grams of carbohydrates'), 
    ('x3', 'grams of protein')
],
'objective_function': '3*x0 + 3*x1 + 5*x2 + 6*x3',
'constraints': [
    'x0 >= 0',
    'x1 >= 0',
    'x2 >= 0',
    'x3 >= 0',
    '1*x0 + 4*x1 + 7*x2 + 17*x3 >= 41',
    '4*x0 + 1*x1 + 7*x2 + 17*x3 >= 41',
    '1*x0 + 4*x1 + 17*x3 >= 41',
    '1*x0 + 7*x2 + 17*x3 >= 62',
    '4*x1 + 7*x2 + 17*x3 >= 62',
    '12*x0 + 6*x1 + 17*x3 >= 62',
    '12*x0 + 15*x2 + 17*x3 >= 62',
    '4*x1 + 15*x2 + 17*x3 >= 62',
    '12*x0 + 6*x1 + 17*x3 >= 62',
    '12*x0 + 15*x2 >= 79',
    '12*x0 + 17*x3 >= 54',
    '15*x2 + 17*x3 >= 59',
    '12*x0 + 6*x1 >= 72',
    '4*x1 + 7*x2 <= 263',
    '1*x0 + 17*x3 <= 90',
    '4*x1 + 17*x3 <= 118',
    '1*x0 + 7*x2 <= 127',
    '1*x0 + 4*x1 <= 133',
    '1*x0 + 4*x1 + 17*x3 <= 210',
    '1*x0 + 7*x2 + 17*x3 <= 261',
    '1*x0 + 4*x1 + 7*x2 <= 130',
    '1*x0 + 4*x1 + 7*x2 + 17*x3 <= 130',
    '12*x0 + 17*x3 <= 229',
    '12*x0 + 6*x1 <= 259',
    '6*x1 + 15*x2 <= 254',
    '12*x0 + 15*x2 <= 225',
    '15*x2 + 17*x3 <= 208',
    '12*x0 + 6*x1 + 15*x2 + 17*x3 <= 208'
]
}
```

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

def optimize_problem():
    model = gurobi.Model()

    # Define variables
    x0 = model.addVar(lb=0, name="milligrams of zinc")
    x1 = model.addVar(lb=0, name="milligrams of vitamin B1")
    x2 = model.addVar(lb=0, name="grams of carbohydrates")
    x3 = model.addVar(lb=0, name="grams of protein")

    # Objective function
    model.setObjective(3*x0 + 3*x1 + 5*x2 + 6*x3, gurobi.GRB.MAXIMIZE)

    # Constraints
    model.addConstr(1*x0 + 4*x1 + 7*x2 + 17*x3 >= 41)
    model.addConstr(4*x0 + 1*x1 + 7*x2 + 17*x3 >= 41)
    model.addConstr(1*x0 + 4*x1 + 17*x3 >= 41)
    model.addConstr(1*x0 + 7*x2 + 17*x3 >= 62)
    model.addConstr(4*x1 + 7*x2 + 17*x3 >= 62)
    model.addConstr(12*x0 + 6*x1 + 17*x3 >= 62)
    model.addConstr(12*x0 + 15*x2 + 17*x3 >= 62)
    model.addConstr(4*x1 + 15*x2 + 17*x3 >= 62)
    model.addConstr(12*x0 + 6*x1 + 17*x3 >= 62)
    model.addConstr(12*x0 + 15*x2 >= 79)
    model.addConstr(12*x0 + 17*x3 >= 54)
    model.addConstr(15*x2 + 17*x3 >= 59)
    model.addConstr(12*x0 + 6*x1 >= 72)
    model.addConstr(4*x1 + 7*x2 <= 263)
    model.addConstr(1*x0 + 17*x3 <= 90)
    model.addConstr(4*x1 + 17*x3 <= 118)
    model.addConstr(1*x0 + 7*x2 <= 127)
    model.addConstr(1*x0 + 4*x1 <= 133)
    model.addConstr(1*x0 + 4*x1 + 17*x3 <= 210)
    model.addConstr(1*x0 + 7*x2 + 17*x3 <= 261)
    model.addConstr(1*x0 + 4*x1 + 7*x2 <= 130)
    model.addConstr(1*x0 + 4*x1 + 7*x2 + 17*x3 <= 130)
    model.addConstr(12*x0 + 17*x3 <= 229)
    model.addConstr(12*x0 + 6*x1 <= 259)
    model.addConstr(6*x1 + 15*x2 <= 254)
    model.addConstr(12*x0 + 15*x2 <= 225)
    model.addConstr(15*x2 + 17*x3 <= 208)
    model.addConstr(12*x0 + 6*x1 + 15*x2 + 17*x3 <= 208)

    model.optimize()

    if model.status == gurobi.GRB.OPTIMAL:
        print("Optimal solution found.")
        print(f"Milligrams of zinc: {x0.varValue}")
        print(f"Milligrams of vitamin B1: {x1.varValue}")
        print(f"Grams of carbohydrates: {x2.varValue}")
        print(f"Grams of protein: {x3.varValue}")
        print(f"Objective function value: {model.objVal}")
    else:
        print("No optimal solution found.")

optimize_problem()
```