```json
{
  "sym_variables": [
    ("x1", "number of trucks"),
    ("x2", "number of vans")
  ],
  "objective_function": "40*x1 + 25*x2",
  "constraints": [
    "15*x1 + 10*x2 <= 300",
    "x1 <= x2",
    "x1 >= 0",
    "x2 >= 0"
  ]
}
```

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

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

# Create variables
trucks = m.addVar(vtype=GRB.INTEGER, name="trucks")
vans = m.addVar(vtype=GRB.INTEGER, name="vans")

# Set objective function
m.setObjective(40 * trucks + 25 * vans, GRB.MAXIMIZE)

# Add constraints
m.addConstr(15 * trucks + 10 * vans <= 300, "Budget")
m.addConstr(trucks <= vans, "Pollution")

# Optimize model
m.optimize()

# Print results
if m.status == GRB.OPTIMAL:
    print(f"Optimal solution found:")
    print(f"Number of trucks: {trucks.x}")
    print(f"Number of vans: {vans.x}")
    print(f"Number of pumpkins transported: {m.objVal}")
elif m.status == GRB.INFEASIBLE:
    print("Model is infeasible.")
else:
    print(f"Optimization ended with status {m.status}")

```
