def test_lower_bound_dict(self):
box_list1 = [ds.Box(3, 5, 2) for i in range(5)]
box_list2 = [ds.Box(2, 2, 2) for i in range(5)]
box_list3 = [ds.Box(2, 2, 4) for i in range(5)]
for box in box_list1:
box.itemName = 'item1'
box.weight = 10
box.maximumWeight = 10
for box in box_list2:
box.itemName = 'item2'
box.weight = 5
box.maximumWeight = 4
for box in box_list3:
box.itemName = 'item3'
box.weight = 4
box.maximumWeight = 4
box_list = box_list1 + box_list2 + box_list3
box_set = ds.BoxSet(box_list)
box_set2 = ds.BoxSet(box_list)
self.assertEqual(True, box_set.__eq__(box_set2))
self.assertEqual(False, box_set.__eq__(ds.BoxSet(box_list[:-1])))
def assign_box_to_bin_v2(box,
current_problem,
i,
not_placed_boxes,
optimal_solutions,
lower_bounds,
optimal=True,
nodes=5000,
optimized=True):
to_place = [box] + current_problem.M[i].boxList
bs = ds.BoxSet(to_place)
optimal_placement = get_soluzione_ottima(bs, optimal_solutions)
if optimal_placement is None:
new_p = current_problem.__copy__()
new_not_placed_boxes = [b for b in not_placed_boxes[1:]]
new_p.boxList = new_not_placed_boxes
new_sbp = new_p.M[i]
new_sbp.add_boxes(box)
h2_result = ds.H2(new_sbp.boxList, new_p.bin, optimized=optimized)
if len(h2_result) == 1:
new_p.M[i] = h2_result[0]
add_optimal_solution(optimal_solutions,
h2_result[0].placement_best_solution)
return new_p, []
#print "sto usando fill bin"
if not optimal:
new_sbp.max_nodes = nodes
new_sbp.m_cut = True
new_sbp.m = 1
single_bin_result = new_sbp.fillBin(optimized=optimized)
if single_bin_result == []:
add_optimal_solution(optimal_solutions,
new_sbp.placement_best_solution)
else:
insert_lower_bound(
lower_bounds, current_problem.M[i].boxList + single_bin_result)
return new_p, single_bin_result
else:
new_p = current_problem.__copy__()
new_not_placed_boxes = [b for b in not_placed_boxes[1:]]
new_p.boxList = new_not_placed_boxes
new_sbp = new_p.M[i]
new_sbp.boxList = optimal_placement.placement
new_sbp.placement_best_solution = optimal_placement.placement
#print "soluzione ottima riutilizzata"
return new_p, []
def add_optimal_solution(optimal_solutions, placement_best_solution):
bs = ds.BoxSet(placement_best_solution)
bs.add_placement(placement_best_solution)
optimal_solutions.append(bs)
def check_lower_bound(lower_bounds, box_list):
if ds.BoxSet(box_list) in lower_bounds:
print "match lower bound"
return False
return True
def insert_lower_bound(lower_bounds, box_list):
bs = ds.BoxSet(box_list)
lower_bounds.append(bs)