```json
{
  "sym_variables": [
    ("x0", "green beans"),
    ("x1", "bananas"),
    ("x2", "chicken thighs"),
    ("x3", "milkshakes")
  ],
  "objective_function": "4*x0 + 2*x1 + 4*x2 + 8*x3",
  "constraints": [
    "18*x2 + 18*x3 >= 34",
    "19*x1 + 18*x3 >= 46",
    "18*x0 + 3*x2 >= 41",
    "17*x0 + 4*x3 >= 30",
    "17*x0 + 11*x1 >= 44",
    "17*x0 + 11*x1 + 4*x3 >= 48",
    "11*x1 + 19*x2 + 4*x3 >= 48",
    "17*x0 + 19*x2 + 4*x3 >= 48",
    "17*x0 + 11*x1 + 4*x3 >= 59",
    "11*x1 + 19*x2 + 4*x3 >= 59",
    "17*x0 + 19*x2 + 4*x3 >= 59",
    "17*x0 + 11*x1 + 4*x3 >= 49",
    "11*x1 + 19*x2 + 4*x3 >= 49",
    "17*x0 + 19*x2 + 4*x3 >= 49",
    "18*x0 + 19*x1 <= 148",
    "19*x1 + 18*x3 <= 97",
    "3*x2 + 18*x3 <= 131",
    "19*x1 + 3*x2 <= 81",
    "18*x0 + 3*x2 <= 66",
    "18*x0 + 19*x1 + 3*x2 + 18*x3 <= 66",
    "19*x2 + 4*x3 <= 125",
    "17*x0 + 4*x3 <= 170",
    "11*x1 + 4*x3 <= 125",
    "17*x0 + 11*x1 + 19*x2 <= 228",
    "17*x0 + 11*x1 + 19*x2 + 4*x3 <= 228",
    "18*x0 + 19*x1 + 3*x2 + 18*x3 <= 193",  % iron upper bound
    "17*x0 + 11*x1 + 19*x2 + 4*x3 <= 237"   % tastiness upper bound

  ]
}
```

```python
import gurobipy as gp

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

# Create variables
green_beans = m.addVar(lb=0, vtype=gp.GRB.CONTINUOUS, name="green_beans")
bananas = m.addVar(lb=0, vtype=gp.GRB.CONTINUOUS, name="bananas")
chicken_thighs = m.addVar(lb=0, vtype=gp.GRB.CONTINUOUS, name="chicken_thighs")
milkshakes = m.addVar(lb=0, vtype=gp.GRB.CONTINUOUS, name="milkshakes")

# Set objective function
m.setObjective(4 * green_beans + 2 * bananas + 4 * chicken_thighs + 8 * milkshakes, gp.GRB.MAXIMIZE)

# Add constraints
m.addConstr(18 * chicken_thighs + 18 * milkshakes >= 34)
m.addConstr(19 * bananas + 18 * milkshakes >= 46)
m.addConstr(18 * green_beans + 3 * chicken_thighs >= 41)
m.addConstr(17 * green_beans + 4 * milkshakes >= 30)
m.addConstr(17 * green_beans + 11 * bananas >= 44)
m.addConstr(17 * green_beans + 11 * bananas + 4 * milkshakes >= 48)
m.addConstr(11 * bananas + 19 * chicken_thighs + 4 * milkshakes >= 48)
m.addConstr(17 * green_beans + 19 * chicken_thighs + 4 * milkshakes >= 48)
m.addConstr(17 * green_beans + 11 * bananas + 4 * milkshakes >= 59)
m.addConstr(11 * bananas + 19 * chicken_thighs + 4 * milkshakes >= 59)
m.addConstr(17 * green_beans + 19 * chicken_thighs + 4 * milkshakes >= 59)
m.addConstr(17 * green_beans + 11 * bananas + 4 * milkshakes >= 49)
m.addConstr(11 * bananas + 19 * chicken_thighs + 4 * milkshakes >= 49)
m.addConstr(17 * green_beans + 19 * chicken_thighs + 4 * milkshakes >= 49)
m.addConstr(18 * green_beans + 19 * bananas <= 148)
m.addConstr(19 * bananas + 18 * milkshakes <= 97)
m.addConstr(3 * chicken_thighs + 18 * milkshakes <= 131)
m.addConstr(19 * bananas + 3 * chicken_thighs <= 81)
m.addConstr(18 * green_beans + 3 * chicken_thighs <= 66)
m.addConstr(18 * green_beans + 19 * bananas + 3 * chicken_thighs + 18 * milkshakes <= 66)
m.addConstr(19 * chicken_thighs + 4 * milkshakes <= 125)
m.addConstr(17 * green_beans + 4 * milkshakes <= 170)
m.addConstr(11 * bananas + 4 * milkshakes <= 125)
m.addConstr(17 * green_beans + 11 * bananas + 19 * chicken_thighs <= 228)
m.addConstr(17 * green_beans + 11 * bananas + 19 * chicken_thighs + 4 * milkshakes <= 228)

# Resource constraints
m.addConstr(18 * green_beans + 19 * bananas + 3 * chicken_thighs + 18 * milkshakes <= 193)
m.addConstr(17 * green_beans + 11 * bananas + 19 * chicken_thighs + 4 * milkshakes <= 237)


# 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)

```
