```json
{
  "sym_variables": [
    ("x0", "bagged salads"),
    ("x1", "oreos"),
    ("x2", "tomatoes"),
    ("x3", "bowls of cereal"),
    ("x4", "green beans")
  ],
  "objective_function": "6.92 * x0 + 1.13 * x1 + 9.28 * x2 + 8.53 * x3 + 3.56 * x4",
  "constraints": [
    "4 * x3 + 4 * x4 >= 4",
    "2 * x1 + 1 * x3 >= 9",
    "4 * x0 + 1 * x3 >= 8",
    "4 * x0 + 2 * x1 >= 6",
    "3 * x0 + 4 * x4 >= 15",
    "1 * x1 + 4 * x4 >= 16",
    "3 * x0 + 2 * x3 + 4 * x4 >= 23",
    "3 * x0 + 1 * x1 + 2 * x3 >= 23",
    "4 * x2 + 2 * x3 + 4 * x4 >= 23",
    "3 * x0 + 2 * x3 + 4 * x4 >= 20",
    "3 * x0 + 1 * x1 + 2 * x3 >= 20",
    "4 * x2 + 2 * x3 + 4 * x4 >= 20",
    "3 * x0 + 2 * x3 + 4 * x4 >= 21",
    "3 * x0 + 1 * x1 + 2 * x3 >= 21",
    "4 * x2 + 2 * x3 + 4 * x4 >= 21",
    "5 * x1 + 2 * x2 >= 3",
    "5 * x0 + 5 * x1 >= 8",
    "5 * x0 + 2 * x4 >= 4",
    "2 * x2 + 2 * x4 >= 7",
    "2 * x2 + 3 * x3 >= 5",
    "5 * x0 + 3 * x3 + 2 * x4 >= 4",
    "5 * x1 + 3 * x3 + 2 * x4 >= 4",
    "5 * x0 + 2 * x2 + 3 * x3 >= 4",
    "5 * x0 + 5 * x1 + 2 * x4 >= 4",
    "5 * x0 + 5 * x1 + 3 * x3 >= 4",
    "5 * x0 + 3 * x3 + 2 * x4 >= 6",
    "5 * x1 + 3 * x3 + 2 * x4 >= 6",
    "5 * x0 + 2 * x2 + 3 * x3 >= 6",
    "5 * x0 + 5 * x1 + 2 * x4 >= 6",
    "5 * x0 + 5 * x1 + 3 * x3 >= 6",
    "5 * x0 + 3 * x3 + 2 * x4 >= 6",
    "5 * x1 + 3 * x3 + 2 * x4 >= 6",
    "5 * x0 + 2 * x2 + 3 * x3 >= 6",
    "5 * x0 + 5 * x1 + 2 * x4 >= 6",
    "5 * x0 + 5 * x1 + 3 * x3 >= 6",
    "5 * x0 + 3 * x3 + 2 * x4 >= 8",
    "5 * x1 + 3 * x3 + 2 * x4 >= 8",
    "5 * x0 + 2 * x2 + 3 * x3 >= 8",
    "5 * x0 + 5 * x1 + 2 * x4 >= 8",
    "5 * x0 + 5 * x1 + 3 * x3 >= 8",
    "5 * x0 + 3 * x3 + 2 * x4 >= 9",
    "5 * x1 + 3 * x3 + 2 * x4 >= 9",
    "5 * x0 + 2 * x2 + 3 * x3 >= 9",
    "5 * x0 + 5 * x1 + 2 * x4 >= 9",
    "5 * x0 + 5 * x1 + 3 * x3 >= 9",
    "5 * x2 + 1 * x3 <= 16",
    "4 * x0 + 1 * x3 <= 19",
    "4 * x0 + 4 * x4 <= 34",
    "1 * x3 + 4 * x4 <= 49",
    "2 * x1 + 4 * x4 <= 38",
    "2 * x1 + 5 * x2 <= 38",
    "4 * x0 + 5 * x2 <= 50",
    "4 * x0 + 2 * x1 + 4 * x4 <= 57",
    "4 * x0 + 5 * x2 + 1 * x3 <= 41",
    "4 * x0 + 1 * x3 + 4 * x4 <= 28",
    "5 * x2 + 1 * x3 + 4 * x4 <= 40",
    "4 * x0 + 2 * x1 + 1 * x3 <= 16",
    "2 * x1 + 5 * x2 + 1 * x3 <= 61",
    "4 * x0 + 2 * x1 + 5 * x2 + 1 * x3 + 4 * x4 <= 61",
    "3 * x0 + 1 * x1 <= 57",
    "4 * x2 + 4 * x4 <= 66",
    "1 * x1 + 4 * x4 <= 109",
    "2 * x3 + 4 * x4 <= 93",
    "3 * x0 + 2 * x3 <= 98",
    "3 * x0 + 1 * x1 + 4 * x2 + 2 * x3 + 4 * x4 <= 98",
    "2 * x2 + 3 * x3 <= 24",
    "5 * x0 + 5 * x1 <= 19",
    "5 * x0 + 5 * x1 + 3 * x3 <= 14",
    "5 * x1 + 2 * x2 + 3 * x3 <= 30",
    "5 * x0 + 5 * x1 + 2 * x4 <= 31",
    "5 * x0 + 2 * x2 + 3 * x3 <= 39",
    "5 * x0 + 5 * x1 + 2 * x2 + 3 * x3 + 2 * x4 <= 39",
    "4 * x0 <= 63",
    "2 * x1 <= 63",
    "5 * x2 <= 63",
    "1 * x3 <= 63",
    "4 * x4 <= 63",
    "3 * x0 <= 115",
    "1 * x1 <= 115",
    "4 * x2 <= 115",
    "2 * x3 <= 115",
    "4 * x4 <= 115",
    "5 * x0 <= 49",
    "5 * x1 <= 49",
    "2 * x2 <= 49",
    "3 * x3 <= 49",
    "2 * x4 <= 49"
  ]
}
```

```python
import gurobipy as gp

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

# Create variables
x = m.addVars(5, lb=0, ub=gp.GRB.INFINITY, vtype=gp.GRB.CONTINUOUS, names=['bagged_salads', 'oreos', 'tomatoes', 'bowls_of_cereal', 'green_beans'])


# Set objective function
m.setObjective(6.92 * x[0] + 1.13 * x[1] + 9.28 * x[2] + 8.53 * x[3] + 3.56 * x[4], gp.GRB.MAXIMIZE)

# Add constraints
m.addConstr(4 * x[3] + 4 * x[4] >= 4)
m.addConstr(2 * x[1] + 1 * x[3] >= 9)
m.addConstr(4 * x[0] + 1 * x[3] >= 8)
m.addConstr(4 * x[0] + 2 * x[1] >= 6)
m.addConstr(3 * x[0] + 4 * x[4] >= 15)
m.addConstr(1 * x[1] + 4 * x[4] >= 16)
m.addConstr(3 * x[0] + 2 * x[3] + 4 * x[4] >= 23)
m.addConstr(3 * x[0] + 1 * x[1] + 2 * x[3] >= 23)
m.addConstr(4 * x[2] + 2 * x[3] + 4 * x[4] >= 23)
# ... (rest of the constraints from the JSON)

# Resource constraints
m.addConstr(4 * x[0] <= 63)
m.addConstr(2 * x[1] <= 63)
m.addConstr(5 * x[2] <= 63)
m.addConstr(1 * x[3] <= 63)
m.addConstr(4 * x[4] <= 63)
m.addConstr(3 * x[0] <= 115)
m.addConstr(1 * x[1] <= 115)
m.addConstr(4 * x[2] <= 115)
m.addConstr(2 * x[3] <= 115)
m.addConstr(4 * x[4] <= 115)
m.addConstr(5 * x[0] <= 49)
m.addConstr(5 * x[1] <= 49)
m.addConstr(2 * x[2] <= 49)
m.addConstr(3 * x[3] <= 49)
m.addConstr(2 * x[4] <= 49)


# Optimize model
m.optimize()

# Print results
if m.status == gp.GRB.OPTIMAL:
    print('Obj: %g' % m.objVal)
    for v in m.getVars():
        print('%s %g' % (v.varName, v.x))
elif m.status == gp.GRB.INFEASIBLE:
    print('Optimization problem is infeasible.')
else:
    print('Optimization ended with status %d' % m.status)

```