Here's the formulation and Gurobi code for the kayak/canoe production optimization problem:

**Decision Variables:**

* `x`: Number of kayaks produced
* `y`: Number of canoes produced

**Objective Function:**

Maximize profit: `300x + 450y`

**Constraints:**

* Assembly time: `60x + 80y <= 8000`
* Quality check time: `15x + 25y <= 4000`
* Non-negativity: `x >= 0`, `y >= 0`


```python
import gurobipy as gp
from gurobipy import GRB

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

# Create variables
x = m.addVar(lb=0, vtype=GRB.CONTINUOUS, name="kayaks")
y = m.addVar(lb=0, vtype=GRB.CONTINUOUS, name="canoes")

# Set objective
m.setObjective(300 * x + 450 * y, GRB.MAXIMIZE)

# Add constraints
m.addConstr(60 * x + 80 * y <= 8000, "assembly")
m.addConstr(15 * x + 25 * y <= 4000, "quality_check")

# Optimize model
m.optimize()

# Print results
if m.status == GRB.OPTIMAL:
    print(f"Optimal Solution Found:")
    print(f"Number of kayaks: {x.x}")
    print(f"Number of canoes: {y.x}")
    print(f"Maximum Profit: ${m.objVal}")
elif m.status == GRB.INFEASIBLE:
    print("Model is infeasible.")
else:
    print(f"Optimization terminated with status {m.status}")

```
