## Step 1: Define the symbolic representation of the problem
The problem involves minimizing an objective function subject to several constraints. The variables are ['sashimi', 'ham sandwiches', 'milkshakes', 'potatoes', 'kale salads'], which we can denote as $x_1, x_2, x_3, x_4, x_5$ respectively.

## Step 2: Convert the objective function into symbolic notation
The objective function to minimize is $9x_1 + 9x_2 + 5x_3 + 9x_4 + 8x_5$.

## 3: Define the constraints in symbolic notation
The constraints given are:
- $11x_2 + 9x_4 \geq 66$
- $8x_1 + 9x_4 \geq 40$
- $17x_3 + 9x_4 \geq 33$
- $11x_2 + 17x_3 + 9x_4 \geq 57$
- $8x_1 + 11x_2 + 18x_5 \geq 57$
- $8x_1 + 17x_3 + 9x_4 \geq 57$
- $11x_2 + 17x_3 + 18x_5 \geq 57$
- $17x_3 + 9x_4 + 18x_5 \geq 57$
- $11x_2 + 17x_3 + 9x_4 \geq 63$
- $8x_1 + 11x_2 + 18x_5 \geq 63$
- $8x_1 + 17x_3 + 9x_4 \geq 63$
- $11x_2 + 17x_3 + 18x_5 \geq 63$
- $17x_3 + 9x_4 + 18x_5 \geq 63$
- $11x_2 + 17x_3 + 9x_4 \geq 43$
- $8x_1 + 11x_2 + 18x_5 \geq 43$
- $8x_1 + 17x_3 + 9x_4 \geq 43$
- $11x_2 + 17x_3 + 18x_5 \geq 43$
- $17x_3 + 9x_4 + 18x_5 \geq 43$
- $11x_2 + 17x_3 + 9x_4 \geq 64$
- $8x_1 + 11x_2 + 18x_5 \geq 64$
- $8x_1 + 17x_3 + 9x_4 \geq 64$
- $11x_2 + 17x_3 + 18x_5 \geq 64$
- $17x_3 + 9x_4 + 18x_5 \geq 64$
- $8x_1 + 11x_2 + 17x_3 + 9x_4 + 18x_5 \geq 64$
- $-10x_1 + x_2 \geq 0$
- $8x_2 - 7x_5 \geq 0$
- $8x_1 + 11x_2 + 18x_5 \leq 150$
- $11x_2 + 9x_4 + 18x_5 \leq 194$
- $8x_1 + 9x_4 + 18x_5 \leq 217$
- $17x_3 + 9x_4 + 18x_5 \leq 282$

## 4: Define the symbolic variables and constraints for the JSON output
```json
{
    'sym_variables': [
        ('x1', 'sashimi'), 
        ('x2', 'ham sandwiches'), 
        ('x3', 'milkshakes'), 
        ('x4', 'potatoes'), 
        ('x5', 'kale salads')
    ], 
    'objective_function': '9*x1 + 9*x2 + 5*x3 + 9*x4 + 8*x5', 
    'constraints': [
        '11*x2 + 9*x4 >= 66',
        '8*x1 + 9*x4 >= 40',
        '17*x3 + 9*x4 >= 33',
        '11*x2 + 17*x3 + 9*x4 >= 57',
        '8*x1 + 11*x2 + 18*x5 >= 57',
        '8*x1 + 17*x3 + 9*x4 >= 57',
        '11*x2 + 17*x3 + 18*x5 >= 57',
        '17*x3 + 9*x4 + 18*x5 >= 57',
        '11*x2 + 17*x3 + 9*x4 >= 63',
        '8*x1 + 11*x2 + 18*x5 >= 63',
        '8*x1 + 17*x3 + 9*x4 >= 63',
        '11*x2 + 17*x3 + 18*x5 >= 63',
        '17*x3 + 9*x4 + 18*x5 >= 63',
        '11*x2 + 17*x3 + 9*x4 >= 43',
        '8*x1 + 11*x2 + 18*x5 >= 43',
        '8*x1 + 17*x3 + 9*x4 >= 43',
        '11*x2 + 17*x3 + 18*x5 >= 43',
        '17*x3 + 9*x4 + 18*x5 >= 43',
        '11*x2 + 17*x3 + 9*x4 >= 64',
        '8*x1 + 11*x2 + 18*x5 >= 64',
        '8*x1 + 17*x3 + 9*x4 >= 64',
        '11*x2 + 17*x3 + 18*x5 >= 64',
        '17*x3 + 9*x4 + 18*x5 >= 64',
        '8*x1 + 11*x2 + 17*x3 + 9*x4 + 18*x5 >= 64',
        '-10*x1 + x2 >= 0',
        '8*x2 - 7*x5 >= 0',
        '8*x1 + 11*x2 + 18*x5 <= 150',
        '11*x2 + 9*x4 + 18*x5 <= 194',
        '8*x1 + 9*x4 + 18*x5 <= 217',
        '17*x3 + 9*x4 + 18*x5 <= 282'
    ]
}
```

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

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

    # Define the variables
    x1 = model.addVar(name="sashimi", vtype=gurobi.GRB.INTEGER)
    x2 = model.addVar(name="ham sandwiches", vtype=gurobi.GRB.INTEGER)
    x3 = model.addVar(name="milkshakes", vtype=gurobi.GRB.INTEGER)
    x4 = model.addVar(name="potatoes", vtype=gurobi.GRB.INTEGER)
    x5 = model.addVar(name="kale salads", vtype=gurobi.GRB.INTEGER)

    # Define the objective function
    model.setObjective(9*x1 + 9*x2 + 5*x3 + 9*x4 + 8*x5, gurobi.GRB.MINIMIZE)

    # Add constraints
    model.addConstr(11*x2 + 9*x4 >= 66)
    model.addConstr(8*x1 + 9*x4 >= 40)
    model.addConstr(17*x3 + 9*x4 >= 33)
    model.addConstr(11*x2 + 17*x3 + 9*x4 >= 57)
    model.addConstr(8*x1 + 11*x2 + 18*x5 >= 57)
    model.addConstr(8*x1 + 17*x3 + 9*x4 >= 57)
    model.addConstr(11*x2 + 17*x3 + 18*x5 >= 57)
    model.addConstr(17*x3 + 9*x4 + 18*x5 >= 57)
    model.addConstr(11*x2 + 17*x3 + 9*x4 >= 63)
    model.addConstr(8*x1 + 11*x2 + 18*x5 >= 63)
    model.addConstr(8*x1 + 17*x3 + 9*x4 >= 63)
    model.addConstr(11*x2 + 17*x3 + 18*x5 >= 63)
    model.addConstr(17*x3 + 9*x4 + 18*x5 >= 63)
    model.addConstr(11*x2 + 17*x3 + 9*x4 >= 43)
    model.addConstr(8*x1 + 11*x2 + 18*x5 >= 43)
    model.addConstr(8*x1 + 17*x3 + 9*x4 >= 43)
    model.addConstr(11*x2 + 17*x3 + 18*x5 >= 43)
    model.addConstr(17*x3 + 9*x4 + 18*x5 >= 43)
    model.addConstr(11*x2 + 17*x3 + 9*x4 >= 64)
    model.addConstr(8*x1 + 11*x2 + 18*x5 >= 64)
    model.addConstr(8*x1 + 17*x3 + 9*x4 >= 64)
    model.addConstr(11*x2 + 17*x3 + 18*x5 >= 64)
    model.addConstr(17*x3 + 9*x4 + 18*x5 >= 64)
    model.addConstr(8*x1 + 11*x2 + 17*x3 + 9*x4 + 18*x5 >= 64)
    model.addConstr(-10*x1 + x2 >= 0)
    model.addConstr(8*x2 - 7*x5 >= 0)
    model.addConstr(8*x1 + 11*x2 + 18*x5 <= 150)
    model.addConstr(11*x2 + 9*x4 + 18*x5 <= 194)
    model.addConstr(8*x1 + 9*x4 + 18*x5 <= 217)
    model.addConstr(17*x3 + 9*x4 + 18*x5 <= 282)

    # Optimize the model
    model.optimize()

    # Print the solution
    if model.status == gurobi.GRB.OPTIMAL:
        print("Objective: ", model.objVal)
        print("sashimi: ", x1.varValue)
        print("ham sandwiches: ", x2.varValue)
        print("milkshakes: ", x3.varValue)
        print("potatoes: ", x4.varValue)
        print("kale salads: ", x5.varValue)
    else:
        print("The model is infeasible")

optimize_problem()
```