```json
{
  "sym_variables": [
    ("x0", "protein bars"),
    ("x1", "granola bars"),
    ("x2", "steaks"),
    ("x3", "chicken breasts"),
    ("x4", "strawberries"),
    ("x5", "tomatoes"),
    ("x6", "sashimi"),
    ("x7", "cornichons")
  ],
  "objective_function": "9.88 * x0 + 7.24 * x1 + 7.18 * x2 + 1.72 * x3 + 8.03 * x4 + 4.13 * x5 + 1.4 * x6 + 4.16 * x7",
  "constraints": [
    "x3 + x4 >= 9",
    "x0 + x2 >= 6",
    "x5 + x7 >= 7",
    "x0 + x7 >= 11",
    "x4 + x6 >= 8",
    "x1 + x7 >= 5",
    "x5 + x6 >= 7",
    "x1 + x2 >= 6",
    "x0 + x1 >= 5",
    "x1 + x5 >= 8",
    "x2 + x7 >= 7",
    "x1 + x4 >= 7",
    "x1 + x3 >= 4",
    "x1 + x6 >= 10",
    "x0 + x6 >= 7",
    "x3 + x7 >= 3",
    "x3 + x6 >= 6",
    "x3 + x5 >= 6",
    "x0 + x1 + x2 + x3 + x4 + x5 + x6 + x7 >= 6",
    "8 * x1 + 2 * x3 >= 11",
    "8 * x1 + 4 * x7 >= 19",
    "4 * x6 + 4 * x7 >= 13",
    "2 * x2 + 2 * x3 >= 12",
    "8 * x1 + 4 * x6 >= 34",
    "5 * x4 + 4 * x7 >= 29",
    "8 * x0 + 4 * x6 >= 12",
    "2 * x2 + 5 * x4 >= 15",
    "8 * x0 + 2 * x2 >= 25",
    "2 * x3 + 4 * x7 >= 28",
    "8 * x1 + 5 * x4 >= 22",
    "8 * x0 + 8 * x1 + 2 * x2 + 2 * x3 + 5 * x4 + 7 * x5 + 4 * x6 + 4 * x7 >= 22",
    "-5 * x0 + 5 * x4 >= 0",
    "7 * x1 - 8 * x7 >= 0",
    "5 * x4 + 8 * x7 <= 37",
    "5 * x3 + 5 * x4 <= 77",
    "x0 + 7 * x5 <= 27",
    "x1 + 3 * x2 <= 93",
    "5 * x4 + 7 * x5 <= 60",
    "x1 + 5 * x3 <= 67",
    "5 * x3 + x6 <= 29",
    "5 * x3 + 7 * x5 <= 75",
    "3 * x2 + 5 * x4 <= 29",
    "8 * x0 + 2 * x2 <= 151",
    "5 * x4 + 4 * x6 <= 41",
    "8 * x1 + 4 * x6 <= 146",
    "8 * x0 + 4 * x7 <= 177",
    "2 * x3 + 4 * x7 <= 161",
    "8 * x0 + 2 * x2 + 4 * x7 <= 114",
    "8 * x1 + 2 * x2 + 2 * x3 <= 67",
    "8 * x1 + 4 * x6 + 4 * x7 <= 102",
    "8 * x1 + 2 * x2 + 5 * x4 <= 172",
    "5 * x4 + 7 * x5 + 4 * x7 <= 160",
    "8 * x0 + 2 * x3 + 5 * x4 <= 86",
    "8 * x1 + 5 * x4 + 4 * x6 <= 86",
    "8 * x0 + 2 * x2 + 2 * x3 <= 47",
    "2 * x3 + 7 * x5 + 4 * x7 <= 140",
    "2 * x3 + 5 * x4 + 7 * x5 <= 191",
    "8 * x0 + 8 * x1 + 7 * x5 <= 252",
    "2 * x2 + 5 * x4 + 7 * x5 <= 126",
    "8 * x0 + 5 * x4 + 4 * x6 <= 245",
    "8 * x0 + 8 * x1 + 2 * x2 <= 61",
    "2 * x3 + 7 * x5 + 4 * x6 <= 230",
    "8 * x1 + 2 * x2 + 7 * x5 <= 170",
    "8 * x0 + 2 * x3 + 4 * x7 <= 244",
    "8 * x1 + 7 * x5 + 4 * x7 <= 233",
    "5 * x4 + 4 * x6 + 4 * x7 <= 74",
    "8 * x0 + 8 * x1 + 4 * x6 <= 241",
    "8 * x1 + 2 * x3 + 4 * x7 <= 247",
    "2 * x2 + 7 * x5 + 4 * x6 <= 34",
    "2 * x2 + 2 * x3 + 7 * x5 <= 59",
    "8 * x0 + 8 * x1 + 2 * x3 <= 209",
    "8 * x0 + 2 * x2 + 7 * x5 <= 78",
    "2 * x2 + 2 * x3 + 4 * x7 <= 255",
    "8 * x1 + 5 * x4 + 4 * x7 <= 255",
    "2 * x2 + 5 * x4 + 4 * x7 <= 271",
    "8 * x0 + 2 * x3 + 4 * x6 <= 184",
    "2 * x2 + 2 * x3 + 5 * x4 <= 238",
    "8 * x0 + 2 * x3 + 7 * x5 <= 61",
    "8 * x0 + 5 * x4 + 7 * x5 <= 150",
    "8 * x0 + 7 * x5 + 4 * x7 <= 222",
    "8 * x0 + 2 * x2 + 5 * x4 <= 81",
    "8 * x0 + 8 * x1 + 4 * x7 <= 115",
    "2 * x2 + 7 * x5 + 4 * x7 <= 36",
    "2 * x2 + 5 * x4 + 4 * x6 <= 160",
    "8 * x1 + 7 * x5 + 4 * x6 <= 53",
    "8 * x1 + 2 * x3 + 4 * x6 <= 150",
    "8 * x1 + 2 * x2 + 4 * x7 <= 263"
  ]
}
```

```python
import gurobipy as gp

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

# Create variables
protein_bars = m.addVar(vtype=gp.GRB.INTEGER, name="protein_bars")
granola_bars = m.addVar(vtype=gp.GRB.INTEGER, name="granola_bars")
steaks = m.addVar(vtype=gp.GRB.INTEGER, name="steaks")
chicken_breasts = m.addVar(vtype=gp.GRB.CONTINUOUS, name="chicken_breasts")
strawberries = m.addVar(vtype=gp.GRB.INTEGER, name="strawberries")
tomatoes = m.addVar(vtype=gp.GRB.INTEGER, name="tomatoes")
sashimi = m.addVar(vtype=gp.GRB.CONTINUOUS, name="sashimi")
cornichons = m.addVar(vtype=gp.GRB.INTEGER, name="cornichons")


# Set objective function
m.setObjective(9.88 * protein_bars + 7.24 * granola_bars + 7.18 * steaks + 1.72 * chicken_breasts + 8.03 * strawberries + 4.13 * tomatoes + 1.4 * sashimi + 4.16 * cornichons, gp.GRB.MINIMIZE)

# Add constraints
m.addConstr(chicken_breasts + strawberries >= 9)
m.addConstr(protein_bars + steaks >= 6)
m.addConstr(tomatoes + cornichons >= 7)
m.addConstr(protein_bars + cornichons >= 11)
m.addConstr(strawberries + sashimi >= 8)
m.addConstr(granola_bars + cornichons >= 5)
m.addConstr(tomatoes + sashimi >= 7)
m.addConstr(granola_bars + steaks >= 6)
m.addConstr(protein_bars + granola_bars >= 5)
m.addConstr(granola_bars + tomatoes >= 8)
m.addConstr(steaks + cornichons >= 7)
m.addConstr(granola_bars + strawberries >= 7)
m.addConstr(granola_bars + chicken_breasts >= 4)
m.addConstr(granola_bars + sashimi >= 10)
m.addConstr(protein_bars + sashimi >= 7)
m.addConstr(chicken_breasts + cornichons >= 3)
m.addConstr(chicken_breasts + sashimi >= 6)
m.addConstr(chicken_breasts + tomatoes >= 6)
m.addConstr(protein_bars + granola_bars + steaks + chicken_breasts + strawberries + tomatoes + sashimi + cornichons >= 6)
# ... (add all other constraints similarly)


# 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("The model is infeasible.")
else:
    print("Optimization ended with status %d" % m.status)

```