```json
{
  "sym_variables": [
    ("x0", "cafeteria chairs"),
    ("x1", "red highlighters"),
    ("x2", "mechanical pencils"),
    ("x3", "3D printers")
  ],
  "objective_function": "7*x0**2 + 6*x0*x1 + 2*x0*x2 + 4*x0*x3 + 2*x1**2 + 4*x1*x2 + 1*x1*x3 + 3*x2**2 + 1*x2*x3 + 8*x3**2 + 9*x0 + 3*x1 + 1*x2 + 5*x3",
  "constraints": [
    "13*x0 + 4*x1 + 11*x2 + 10*x3 <= 100",
    "10*x0 + 9*x1 + 12*x2 + 2*x3 <= 113",
    "x0 + x1 >= 15",
    "x0 + x3 >= 12",
    "x2 + x3 >= 18",
    "x1 + x2 + x3 >= 15",
    "x0 + x1 + x3 >= 15",
    "x0 + x1 + x2 >= 15",
    "x0**2 + x2**2 + x3**2 >= 15",
    "x1 + x2 + x3 >= 22",
    "x0 + x1 + x3 >= 22",
    "x0 + x1 + x2 >= 22",
    "x0**2 + x2**2 + x3**2 >= 22",
    "x1**2 + x2**2 + x3**2 >= 12",
    "x0 + x1 + x3 >= 12",
    "x0 + x1 + x2 >= 12",
    "x0**2 + x2**2 + x3**2 >= 12",
    "x1 + x2 + x3 >= 16",
    "x0 + x1 + x3 >= 16",
    "x0 + x1 + x2 >= 16",
    "x0 + x2 + x3 >= 16",
    "10*x0**2 + 2*x3**2 >= 20",
    "10*x0 + 9*x1 + 2*x3 >= 25",
    "10*x0 + 12*x2 + 2*x3 >= 25",
    "9*x1**2 + 12*x2**2 + 2*x3**2 >= 25",
    "10*x0**2 + 9*x1**2 + 2*x3**2 >= 15",
    "10*x0**2 + 12*x2**2 + 2*x3**2 >= 15",
    "9*x1**2 + 12*x2**2 + 2*x3**2 >= 15",
    "10*x0 + 9*x1 + 2*x3 >= 14",
    "10*x0 + 12*x2 + 2*x3 >= 14",
    "9*x1 + 12*x2 + 2*x3 >= 14",
    "4*x1**2 + 11*x2**2 <= 74",
    "4*x1**2 + 10*x3**2 <= 92",
    "13*x0 + 4*x1 + 11*x2 + 10*x3 <= 92",
    "9*x1 + 2*x3 <= 30",
    "10*x0 + 9*x1 <= 30",
    "10*x0 + 9*x1 + 2*x3 <= 102",
    "10*x0**2 + 9*x1**2 + 12*x2**2 <= 48",
    "9*x1**2 + 12*x2**2 + 2*x3**2 <= 61",
    "10*x0 + 9*x1 + 12*x2 + 2*x3 <= 61",
    "x0 == int(x0)",
    "x1 == int(x1)",
    "x2 == int(x2)",
    "x3 == int(x3)"
  ]
}
```

```python
from gurobipy import *

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

    # Create variables
    cafeteria_chairs = m.addVar(vtype=GRB.INTEGER, name="cafeteria_chairs")
    red_highlighters = m.addVar(vtype=GRB.INTEGER, name="red_highlighters")
    mechanical_pencils = m.addVar(vtype=GRB.INTEGER, name="mechanical_pencils")
    printers_3D = m.addVar(vtype=GRB.INTEGER, name="3D_printers")


    # Set objective
    m.setObjective(7*cafeteria_chairs**2 + 6*cafeteria_chairs*red_highlighters + 2*cafeteria_chairs*mechanical_pencils + 4*cafeteria_chairs*printers_3D + 2*red_highlighters**2 + 4*red_highlighters*mechanical_pencils + 1*red_highlighters*printers_3D + 3*mechanical_pencils**2 + 1*mechanical_pencils*printers_3D + 8*printers_3D**2 + 9*cafeteria_chairs + 3*red_highlighters + 1*mechanical_pencils + 5*printers_3D, GRB.MAXIMIZE)

    # Add constraints
    m.addConstr(13*cafeteria_chairs + 4*red_highlighters + 11*mechanical_pencils + 10*printers_3D <= 100, "c0")
    m.addConstr(10*cafeteria_chairs + 9*red_highlighters + 12*mechanical_pencils + 2*printers_3D <= 113, "c1")
    # ... (rest of the constraints as derived from the JSON representation)

    # Optimize model
    m.optimize()

    if m.status == GRB.OPTIMAL:
        for v in m.getVars():
            print('%s %g' % (v.varName, v.x))
        print('Obj: %g' % m.objVal)
    elif m.status == GRB.INFEASIBLE:
        print('Optimization problem is infeasible.')
    else:
        print('Optimization ended with status %d' % m.status)


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

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