```json
{
  "sym_variables": [
    ("x0", "oreos"),
    ("x1", "kiwis"),
    ("x2", "slices of pizza")
  ],
  "objective_function": "8*x0 + 8*x1 + 7*x2",
  "constraints": [
    "1*x0 + 12*x2 >= 61",
    "1*x0 + 23*x1 >= 90",
    "1*x0 + 23*x1 + 12*x2 >= 74",
    "7*x1 + 6*x2 >= 59",
    "22*x0 + 7*x1 + 6*x2 >= 59",
    "-8*x1 + 7*x2 >= 0",
    "3*x0 - 4*x1 >= 0",
    "-4*x0 + 5*x2 >= 0",
    "23*x1 + 12*x2 <= 170",
    "1*x0 + 23*x1 <= 358",
    "22*x0 + 6*x2 <= 115",
    "x0 >= 0",
    "x1 >= 0",
    "x2 >= 0",
    "1*x0 <= 429",
    "22*x0 + 7*x1 + 6*x2 <= 316"

  ]
}
```

```python
import gurobipy as gp

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

    # Create variables
    oreos = model.addVar(lb=0, vtype=gp.GRB.CONTINUOUS, name="oreos")
    kiwis = model.addVar(lb=0, vtype=gp.GRB.CONTINUOUS, name="kiwis")
    pizza_slices = model.addVar(lb=0, vtype=gp.GRB.CONTINUOUS, name="pizza_slices")


    # Set objective function
    model.setObjective(8 * oreos + 8 * kiwis + 7 * pizza_slices, gp.GRB.MINIMIZE)

    # Add constraints
    model.addConstr(1 * oreos + 12 * pizza_slices >= 61, "c0")
    model.addConstr(1 * oreos + 23 * kiwis >= 90, "c1")
    model.addConstr(1 * oreos + 23 * kiwis + 12 * pizza_slices >= 74, "c2")
    model.addConstr(7 * kiwis + 6 * pizza_slices >= 59, "c3")
    model.addConstr(22 * oreos + 7 * kiwis + 6 * pizza_slices >= 59, "c4")
    model.addConstr(-8 * kiwis + 7 * pizza_slices >= 0, "c5")
    model.addConstr(3 * oreos - 4 * kiwis >= 0, "c6")
    model.addConstr(-4 * oreos + 5 * pizza_slices >= 0, "c7")
    model.addConstr(23 * kiwis + 12 * pizza_slices <= 170, "c8")
    model.addConstr(1 * oreos + 23 * kiwis <= 358, "c9")
    model.addConstr(22 * oreos + 6 * pizza_slices <= 115, "c10")
    model.addConstr(1 * oreos <= 429, "c11")
    model.addConstr(22 * oreos + 7 * kiwis + 6 * pizza_slices <= 316, "c12")



    # Optimize model
    model.optimize()

    if model.status == gp.GRB.OPTIMAL:
        print('Obj: %g' % model.objVal)
        print('oreos:', oreos.x)
        print('kiwis:', kiwis.x)
        print('pizza_slices:', pizza_slices.x)
    elif model.status == gp.GRB.INFEASIBLE:
        print('The model is infeasible.')
    else:
        print('Optimization ended with status %d' % model.status)


except gp.GurobiError as e:
    print('Error code ' + str(e.errno) + ': ' + str(e))

except AttributeError:
    print('Encountered an attribute error')
```