```json
{
  "sym_variables": [
    ("x0", "chicken breasts"),
    ("x1", "kale salads"),
    ("x2", "cherry pies"),
    ("x3", "blueberry pies")
  ],
  "objective_function": "3.85*x0 + 4.14*x1 + 9.8*x2 + 3.1*x3",
  "constraints": [
    "1*x0 + 10*x1 >= 13",
    "10*x1 + 10*x3 >= 18",
    "3*x2 + 10*x3 >= 9",
    "1*x0 + 3*x2 >= 27",
    "1*x0 + 10*x1 + 3*x2 >= 23",
    "10*x1 + 3*x2 + 10*x3 >= 23",
    "1*x0 + 10*x1 + 3*x2 >= 26",
    "10*x1 + 3*x2 + 10*x3 >= 26",
    "1*x0 + 10*x1 + 3*x2 + 10*x3 >= 26",
    "8*x1 + 6*x3 >= 26",
    "8*x0 + 7*x2 >= 26",
    "7*x2 + 6*x3 >= 26",
    "8*x0 + 6*x3 >= 20",
    "8*x0 + 8*x1 + 7*x2 + 6*x3 >= 20",
    "10*x1 + 6*x2 >= 20",
    "7*x0 + 6*x2 >= 33",
    "6*x2 + 9*x3 >= 31",
    "7*x0 + 9*x3 >= 28",
    "7*x0 + 10*x1 >= 22",
    "7*x0 + 6*x2 + 9*x3 >= 19",
    "7*x0 + 10*x1 + 6*x2 + 9*x3 >= 19",
    "2*x0 - 2*x3 >= 0",
    "10*x1 - 5*x2 >= 0",
    "1*x0 + 10*x1 <= 65",
    "3*x2 + 10*x3 <= 45",
    "10*x1 + 10*x3 <= 91",
    "10*x1 + 3*x2 + 10*x3 <= 104",
    "1*x0 + 10*x1 + 10*x3 <= 104",
    "8*x0 + 7*x2 <= 125",
    "7*x2 + 6*x3 <= 78",
    "7*x0 + 9*x3 <= 60",
    "7*x0 + 10*x1 + 9*x3 <= 67",
    "1*x0 <= 110/1",
    "10*x1 <= 110/10",
    "3*x2 <= 110/3",
    "10*x3 <= 110/10",
    "8*x0 <= 169/8",
    "8*x1 <= 169/8",
    "7*x2 <= 169/7",
    "6*x3 <= 169/6",
    "7*x0 <= 145/7",
    "10*x1 <= 145/10",
    "6*x2 <= 145/6",
    "9*x3 <= 145/9"

  ]
}
```

```python
import gurobipy as gp

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

# Create variables
chicken_breasts = m.addVar(lb=0, vtype=gp.GRB.CONTINUOUS, name="chicken_breasts")
kale_salads = m.addVar(lb=0, vtype=gp.GRB.CONTINUOUS, name="kale_salads")
cherry_pies = m.addVar(lb=0, vtype=gp.GRB.CONTINUOUS, name="cherry_pies")
blueberry_pies = m.addVar(lb=0, vtype=gp.GRB.CONTINUOUS, name="blueberry_pies")


# Set objective function
m.setObjective(3.85 * chicken_breasts + 4.14 * kale_salads + 9.8 * cherry_pies + 3.1 * blueberry_pies, gp.GRB.MINIMIZE)

# Add constraints
m.addConstr(chicken_breasts + 10 * kale_salads >= 13)
m.addConstr(10 * kale_salads + 10 * blueberry_pies >= 18)
m.addConstr(3 * cherry_pies + 10 * blueberry_pies >= 9)
m.addConstr(chicken_breasts + 3 * cherry_pies >= 27)
m.addConstr(chicken_breasts + 10 * kale_salads + 3 * cherry_pies >= 23)
m.addConstr(10 * kale_salads + 3 * cherry_pies + 10 * blueberry_pies >= 23)
m.addConstr(chicken_breasts + 10 * kale_salads + 3 * cherry_pies >= 26)
m.addConstr(10 * kale_salads + 3 * cherry_pies + 10 * blueberry_pies >= 26)
m.addConstr(chicken_breasts + 10 * kale_salads + 3 * cherry_pies + 10 * blueberry_pies >= 26)
m.addConstr(8 * kale_salads + 6 * blueberry_pies >= 26)
m.addConstr(8 * chicken_breasts + 7 * cherry_pies >= 26)
m.addConstr(7 * cherry_pies + 6 * blueberry_pies >= 26)
m.addConstr(8 * chicken_breasts + 6 * blueberry_pies >= 20)
m.addConstr(8 * chicken_breasts + 8 * kale_salads + 7 * cherry_pies + 6 * blueberry_pies >= 20)
m.addConstr(10 * kale_salads + 6 * cherry_pies >= 20)
m.addConstr(7 * chicken_breasts + 6 * cherry_pies >= 33)
m.addConstr(6 * cherry_pies + 9 * blueberry_pies >= 31)
m.addConstr(7 * chicken_breasts + 9 * blueberry_pies >= 28)
m.addConstr(7 * chicken_breasts + 10 * kale_salads >= 22)
m.addConstr(7 * chicken_breasts + 6 * cherry_pies + 9 * blueberry_pies >= 19)
m.addConstr(7 * chicken_breasts + 10 * kale_salads + 6 * cherry_pies + 9 * blueberry_pies >= 19)
m.addConstr(2 * chicken_breasts - 2 * blueberry_pies >= 0)
m.addConstr(10 * kale_salads - 5 * cherry_pies >= 0)
m.addConstr(chicken_breasts + 10 * kale_salads <= 65)
m.addConstr(3 * cherry_pies + 10 * blueberry_pies <= 45)
m.addConstr(10 * kale_salads + 10 * blueberry_pies <= 91)
m.addConstr(10 * kale_salads + 3 * cherry_pies + 10 * blueberry_pies <= 104)
m.addConstr(chicken_breasts + 10 * kale_salads + 10 * blueberry_pies <= 104)
m.addConstr(8 * chicken_breasts + 7 * cherry_pies <= 125)
m.addConstr(7 * cherry_pies + 6 * blueberry_pies <= 78)
m.addConstr(7 * chicken_breasts + 9 * blueberry_pies <= 60)
m.addConstr(7 * chicken_breasts + 10 * kale_salads + 9 * blueberry_pies <= 67)


m.addConstr(chicken_breasts <= 110)
m.addConstr(10*kale_salads <= 110)
m.addConstr(3*cherry_pies <= 110)
m.addConstr(10*blueberry_pies <= 110)

m.addConstr(8*chicken_breasts <= 169)
m.addConstr(8*kale_salads <= 169)
m.addConstr(7*cherry_pies <= 169)
m.addConstr(6*blueberry_pies <= 169)

m.addConstr(7*chicken_breasts <= 145)
m.addConstr(10*kale_salads <= 145)
m.addConstr(6*cherry_pies <= 145)
m.addConstr(9*blueberry_pies <= 145)



# 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)

```