## Step 1: Define the symbolic representation of the variables
The variables are ['sashimi', 'cantaloupes', 'cornichons', 'black beans', 'oreos'] which can be represented symbolically as ['x0', 'x1', 'x2', 'x3', 'x4'].

## Step 2: Convert the natural language description into a symbolic representation
The symbolic representation of the variables is:
- x0: sashimi
- x1: cantaloupes
- x2: cornichons
- x3: black beans
- x4: oreos

## Step 3: Define the objective function in symbolic notation
The objective function to maximize is: 
\[ x0^2 + 5x0x2 + 9x0x3 + 4x0x4 + 5x1x2 + 2x1x3 + 9x2x3 + 5x2x4 + x1 + 2x2 \]

## 4: List the constraints in symbolic notation
The constraints are:
- \( 13x0 + 23x1 + 19x2 + 2x3 + 12x4 \leq 369 \) (calcium constraint)
- \( 26x0 + 25x1 + 24x2 + 23x3 + 9x4 \leq 348 \) (fat constraint)
- \( 13x0 + 19x2 \geq 43 \) (calcium from sashimi and cornichons)
- \( 23x3 + 9x4 \geq 29 \) (fat from black beans and oreos)
- \( 23x1 + 2x3 \leq 76 \) (calcium from cantaloupes and black beans)
- \( 13^2x0^2 + 2^2x3^2 \leq 119 \) (calcium from sashimi squared and black beans squared)
- \( 2^2x3^2 + 12^2x4^2 \leq 312 \) (calcium from black beans squared and oreos squared)
- \( 13x0 + 23x1 + 19x2 + 2x3 + 12x4 \leq 312 \) (total calcium constraint)
- \( 24x2 + 23x3 \leq 342 \) (fat from cornichons and black beans)
- \( 25x1 + 24x2 \leq 269 \) (fat from cantaloupes and cornichons)
- \( 25^2x1^2 + 9^2x4^2 \leq 206 \) (fat from cantaloupes squared and oreos squared)
- \( 25x1 + 23x3 \leq 328 \) (fat from cantaloupes and black beans)
- \( 23x3 + 9x4 \leq 88 \) (fat from black beans and oreos)
- \( 26x0 + 25x1 \leq 76 \) (fat from sashimi and cantaloupes)
- \( 24x2 + 9x4 \leq 213 \) (fat from cornichons and oreos)
- \( 26x0 + 25x1 + 24x2 + 23x3 + 9x4 \leq 213 \) (total fat constraint)

## 5: Create the Gurobi model and variables
We will use Gurobi to solve this optimization problem.

## 6: Implement the Gurobi code
```python
import gurobi as gp

# Create a new model
m = gp.Model("optimization_problem")

# Define the variables
x0 = m.addVar(name="sashimi", lb=-gp.GRB.INFINITY, ub=gp.GRB.INFINITY)
x1 = m.addVar(name="cantaloupes", lb=-gp.GRB.INFINITY, ub=gp.GRB.INFINITY)
x2 = m.addVar(name="cornichons", lb=-gp.GRB.INFINITY, ub=gp.GRB.INFINITY)
x3 = m.addVar(name="black_beans", lb=-gp.GRB.INFINITY, ub=gp.GRB.INFINITY)
x4 = m.addVar(name="oreos", lb=-gp.GRB.INFINITY, ub=gp.GRB.INFINITY)

# Objective function
m.setObjective(x0**2 + 5*x0*x2 + 9*x0*x3 + 4*x0*x4 + 5*x1*x2 + 2*x1*x3 + 9*x2*x3 + 5*x2*x4 + x1 + 2*x2, gp.GRB.MAXIMIZE)

# Constraints
m.addConstr(13*x0 + 23*x1 + 19*x2 + 2*x3 + 12*x4 <= 369)
m.addConstr(26*x0 + 25*x1 + 24*x2 + 23*x3 + 9*x4 <= 348)
m.addConstr(13*x0 + 19*x2 >= 43)
m.addConstr(23*x3 + 9*x4 >= 29)
m.addConstr(23*x1 + 2*x3 <= 76)
m.addConstr((13**2)*x0**2 + (2**2)*x3**2 <= 119)
m.addConstr((2**2)*x3**2 + (12**2)*x4**2 <= 312)
m.addConstr(13*x0 + 23*x1 + 19*x2 + 2*x3 + 12*x4 <= 312)
m.addConstr(24*x2 + 23*x3 <= 342)
m.addConstr(25*x1 + 24*x2 <= 269)
m.addConstr((25**2)*x1**2 + (9**2)*x4**2 <= 206)
m.addConstr(25*x1 + 23*x3 <= 328)
m.addConstr(23*x3 + 9*x4 <= 88)
m.addConstr(26*x0 + 25*x1 <= 76)
m.addConstr(24*x2 + 9*x4 <= 213)
m.addConstr(26*x0 + 25*x1 + 24*x2 + 23*x3 + 9*x4 <= 213)

# Solve the model
m.optimize()

# Print the solution
if m.status == gp.GRB.OPTIMAL:
    print("Objective: ", m.objVal)
    print("sashimi: ", x0.varValue)
    print("cantaloupes: ", x1.varValue)
    print("cornichons: ", x2.varValue)
    print("black beans: ", x3.varValue)
    print("oreos: ", x4.varValue)
else:
    print("The model is infeasible")
```

## 7: Symbolic representation of the problem
```json
{
    'sym_variables': [
        ('x0', 'sashimi'), 
        ('x1', 'cantaloupes'), 
        ('x2', 'cornichons'), 
        ('x3', 'black beans'), 
        ('x4', 'oreos')
    ], 
    'objective_function': 'x0^2 + 5*x0*x2 + 9*x0*x3 + 4*x0*x4 + 5*x1*x2 + 2*x1*x3 + 9*x2*x3 + 5*x2*x4 + x1 + 2*x2', 
    'constraints': [
        '13*x0 + 23*x1 + 19*x2 + 2*x3 + 12*x4 <= 369',
        '26*x0 + 25*x1 + 24*x2 + 23*x3 + 9*x4 <= 348',
        '13*x0 + 19*x2 >= 43',
        '23*x3 + 9*x4 >= 29',
        '23*x1 + 2*x3 <= 76',
        '(13^2)*x0^2 + (2^2)*x3^2 <= 119',
        '(2^2)*x3^2 + (12^2)*x4^2 <= 312',
        '13*x0 + 23*x1 + 19*x2 + 2*x3 + 12*x4 <= 312',
        '24*x2 + 23*x3 <= 342',
        '25*x1 + 24*x2 <= 269',
        '(25^2)*x1^2 + (9^2)*x4^2 <= 206',
        '25*x1 + 23*x3 <= 328',
        '23*x3 + 9*x4 <= 88',
        '26*x0 + 25*x1 <= 76',
        '24*x2 + 9*x4 <= 213',
        '26*x0 + 25*x1 + 24*x2 + 23*x3 + 9*x4 <= 213'
    ]
}
```