```json
{
  "sym_variables": [
    ("x0", "blue highlighters"),
    ("x1", "staplers"),
    ("x2", "cafeteria chairs")
  ],
  "objective_function": "5*x0 + 8*x1 + 3*x2",
  "constraints": [
    "3.05*x0 + 0.11*x1 + 7.99*x2 <= 67",
    "0.11*x1 + 7.99*x2 <= 61",
    "3.05*x0 + 7.99*x2 <= 22",
    "3.05*x0 + 0.11*x1 + 7.99*x2 <= 57",
    "x0, x1, x2 are integers",
    "x0 >= 0",
    "x1 >= 0",
    "x2 >= 0"

  ]
}
```

```python
import gurobipy as gp

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

# Create variables
blue_highlighters = model.addVar(vtype=gp.GRB.INTEGER, name="blue_highlighters")
staplers = model.addVar(vtype=gp.GRB.INTEGER, name="staplers")
cafeteria_chairs = model.addVar(vtype=gp.GRB.INTEGER, name="cafeteria_chairs")


# Set objective function
model.setObjective(5 * blue_highlighters + 8 * staplers + 3 * cafeteria_chairs, gp.GRB.MAXIMIZE)

# Add constraints
model.addConstr(3.05 * blue_highlighters + 0.11 * staplers + 7.99 * cafeteria_chairs <= 67, "storage_space")
model.addConstr(0.11 * staplers + 7.99 * cafeteria_chairs <= 61, "staplers_chairs_space")
model.addConstr(3.05 * blue_highlighters + 7.99 * cafeteria_chairs <= 22, "highlighters_chairs_space")
model.addConstr(3.05 * blue_highlighters + 0.11 * staplers + 7.99 * cafeteria_chairs <= 57, "total_space_alt")


# Optimize model
model.optimize()

# Print results
if model.status == gp.GRB.OPTIMAL:
    print(f"Optimal objective value: {model.objVal}")
    print(f"Blue Highlighters: {blue_highlighters.x}")
    print(f"Staplers: {staplers.x}")
    print(f"Cafeteria Chairs: {cafeteria_chairs.x}")
elif model.status == gp.GRB.INFEASIBLE:
    print("The model is infeasible.")
else:
    print(f"Optimization ended with status {model.status}")

```
