## Problem Description and Formulation

The problem is an optimization problem with two variables: `lanyards` and `color_printers`. The objective is to minimize the function $3 \cdot lanyards + 3 \cdot color\_printers$.

The problem has several constraints:

1. The usefulness rating of `lanyards` is 4.
2. `lanyards` each take up 23 sq. ft in storage.
3. `color_printers` have a usefulness rating of 23.
4. `color_printers` occupy 9 sq. ft of storage space each.
5. The total combined usefulness rating from `lanyards` and `color_printers` must be at least 61.
6. The total combined storage space occupied by `lanyards` and `color_printers` must be at least 48 sq. ft.
7. $6 \cdot lanyards - 6 \cdot color\_printers \geq 0$.
8. The total combined usefulness rating from `lanyards` and `color_printers` must be at most 79.
9. The total combined storage space occupied by `lanyards` and `color_printers` must be at most 81 sq. ft.
10. `lanyards` and `color_printers` must be integers.

## Gurobi Code

```python
import gurobi

# Create a new Gurobi model
model = gurobi.Model()

# Define the variables
lanyards = model.addVar(name="lanyards", vtype=gurobi.GRB.INTEGER)
color_printers = model.addVar(name="color_printers", vtype=gurobi.GRB.INTEGER)

# Objective function: minimize 3 * lanyards + 3 * color_printers
model.setObjective(3 * lanyards + 3 * color_printers, gurobi.GRB.MINIMIZE)

# Constraints
model.addConstr(4 * lanyards + 23 * color_printers >= 61)  # usefulness rating >= 61
model.addConstr(23 * lanyards + 9 * color_printers >= 48)  # storage space >= 48
model.addConstr(6 * lanyards - 6 * color_printers >= 0)  # 6 * lanyards - 6 * color_printers >= 0
model.addConstr(4 * lanyards + 23 * color_printers <= 79)  # usefulness rating <= 79
model.addConstr(23 * lanyards + 9 * color_printers <= 81)  # storage space <= 81

# Optimize the model
model.optimize()

# Print the solution
if model.status == gurobi.GRB.OPTIMAL:
    print("Optimal solution found.")
    print(f"Lanyards: {lanyards.varValue}")
    print(f"Color Printers: {color_printers.varValue}")
    print(f"Objective: {model.objVal}")
else:
    print("No optimal solution found.")
```