binpacking.py

from ortools.sat.python import cp_model
from typing import NamedTuple

class Box(NamedTuple):
    weight: int

class Truck(NamedTuple):
    capacity: int

trucks = [Truck(3000), Truck(5000), Truck(8000)]
boxes = [Box(3000), Box(3000), Box(4000), Box(2000)]

#trucks = [Truck(5), Truck(5), Truck(5)]
#boxes = [Box(2), Box(2), Box(3), Box(1), Box(1)]

model = cp_model.CpModel()

truckInUse = [ model.NewBoolVar(f"truck {ti} in use?") for ti in range(len(trucks)) ]
vars = {}
for ti in range(len(trucks)):
    for bi in range(len(boxes)):
        vars[(bi,ti)] = model.NewBoolVar(f"box {bi} in truck {ti}?")

for bi in range(len(boxes)):
    model.AddExactlyOne([vars[(bi,ti)] for ti in range(len(trucks))])

for ti in range(len(trucks)):
    model.Add(
        sum(
            [vars[(bi,ti)] * boxes[bi].weight for bi in range(len(boxes))]
        ) <= trucks[ti].capacity * truckInUse[ti]
    )


model.Minimize(sum(truckInUse))

solver = cp_model.CpSolver()
solver.Solve(model)

for ti in range(len(trucks)):
    print(f"boxes in truck {ti} ({trucks[ti].capacity}):")
    for bi in range(len(boxes)):
        v = solver.Value(vars[(bi,ti)])
        if v:
            print(f"  {bi} ({boxes[bi].weight})")