```json
{
  "sym_variables": [
    ("x0", "tomatoes"),
    ("x1", "apple pies"),
    ("x2", "rotisserie chickens")
  ],
  "objective_function": "2*x0 + 3*x1 + 6*x2",
  "constraints": [
    "17*x1 + 11*x2 >= 26",
    "17*x0 + 17*x1 + 11*x2 >= 26",
    "18*x0 + 11*x1 >= 41",
    "18*x0 + 10*x2 >= 49",
    "18*x0 + 11*x1 + 10*x2 >= 49",
    "1*x0 + 1*x1 >= 17",
    "1*x0 + 19*x2 >= 32",
    "1*x0 + 1*x1 + 19*x2 >= 32",
    "18*x0 + 17*x1 >= 50",
    "17*x1 + 15*x2 >= 67",
    "18*x0 + 17*x1 + 15*x2 >= 67",
    "-1*x0 + 9*x1 >= 0",
    "-1*x1 + 1*x2 >= 0",
    "17*x1 + 11*x2 <= 159",
    "17*x0 + 17*x1 + 11*x2 <= 160",
    "18*x0 + 15*x2 <= 89",
    "17*x0 <= 217",
    "18*x0 <= 147",
    "1*x0 <= 135",
    "18*x0 <= 255",
    "17*x1 <= 217",
    "11*x1 <= 147",
    "1*x1 <= 135",
    "17*x1 <= 255",
    "11*x2 <= 217",
    "10*x2 <= 147",
    "19*x2 <= 135",
    "15*x2 <= 255"
  ]
}
```

```python
import gurobipy as gp

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

# Create variables
tomatoes = m.addVar(vtype=gp.GRB.INTEGER, name="tomatoes")
apple_pies = m.addVar(vtype=gp.GRB.CONTINUOUS, name="apple_pies")
rotisserie_chickens = m.addVar(vtype=gp.GRB.CONTINUOUS, name="rotisserie_chickens")

# Set objective function
m.setObjective(2 * tomatoes + 3 * apple_pies + 6 * rotisserie_chickens, gp.GRB.MINIMIZE)

# Add constraints
m.addConstr(17 * apple_pies + 11 * rotisserie_chickens >= 26)
m.addConstr(17 * tomatoes + 17 * apple_pies + 11 * rotisserie_chickens >= 26)
m.addConstr(18 * tomatoes + 11 * apple_pies >= 41)
m.addConstr(18 * tomatoes + 10 * rotisserie_chickens >= 49)
m.addConstr(18 * tomatoes + 11 * apple_pies + 10 * rotisserie_chickens >= 49)
m.addConstr(1 * tomatoes + 1 * apple_pies >= 17)
m.addConstr(1 * tomatoes + 19 * rotisserie_chickens >= 32)
m.addConstr(1 * tomatoes + 1 * apple_pies + 19 * rotisserie_chickens >= 32)
m.addConstr(18 * tomatoes + 17 * apple_pies >= 50)
m.addConstr(17 * apple_pies + 15 * rotisserie_chickens >= 67)
m.addConstr(18 * tomatoes + 17 * apple_pies + 15 * rotisserie_chickens >= 67)
m.addConstr(-1 * tomatoes + 9 * apple_pies >= 0)
m.addConstr(-1 * apple_pies + 1 * rotisserie_chickens >= 0)
m.addConstr(17 * apple_pies + 11 * rotisserie_chickens <= 159)
m.addConstr(17 * tomatoes + 17 * apple_pies + 11 * rotisserie_chickens <= 160)
m.addConstr(18 * tomatoes + 15 * rotisserie_chickens <= 89)

# Resource Constraints
m.addConstr(17 * tomatoes <= 217)
m.addConstr(18 * tomatoes <= 147)
m.addConstr(1 * tomatoes <= 135)
m.addConstr(18 * tomatoes <= 255)
m.addConstr(17 * apple_pies <= 217)
m.addConstr(11 * apple_pies <= 147)
m.addConstr(1 * apple_pies <= 135)
m.addConstr(17 * apple_pies <= 255)
m.addConstr(11 * rotisserie_chickens <= 217)
m.addConstr(10 * rotisserie_chickens <= 147)
m.addConstr(19 * rotisserie_chickens <= 135)
m.addConstr(15 * rotisserie_chickens <= 255)


# Optimize model
m.optimize()

# Print results
if m.status == gp.GRB.OPTIMAL:
    print('Obj: %g' % m.objVal)
    print('tomatoes:', tomatoes.x)
    print('apple_pies:', apple_pies.x)
    print('rotisserie_chickens:', rotisserie_chickens.x)
elif m.status == gp.GRB.INFEASIBLE:
    print('The problem is infeasible.')
else:
    print('The problem could not be solved to optimality.')

```