always-cautious/ortools-clone
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

improve 2d packing example

Browse Source
This commit is contained in:
Laurent Perron
2021-11-14 19:18:00 +01:00
parent 74dccbb97d
commit 503a4c3bd2
1 changed files with 101 additions and 96 deletions
Download Patch File Download Diff File Expand all files Collapse all files

197
examples/python/packing_2d_sat.py
View File

@@ -37,6 +37,10 @@ flags.DEFINE_string('params', 'num_search_workers:16,log_search_progress:true',
flags.DEFINE_string('model', 'rotation', '\'duplicate\' or \'rotation\'')
def scale_double(value):
return int(round(value * 1000.0))
def build_data():
"""Build the data frame."""
data = """
@@ -57,15 +61,18 @@ def build_data():
print('Input data')
print(data)
height = 20
width = 30
max_height = 20
max_width = 30
print(f'Container width:{width} height:{height}')
print(f'Container max_width:{max_width} max_height:{max_height}')
print(f'#Items: {len(data.index)}')
return (data, height, width)
return (data, max_height, max_width)
def solve_with_duplicate_items(data, height, width):
# pytype: disable=wrong-arg-types
def solve_with_duplicate_items(data, max_height, max_width):
"""Solve the problem by building 2 items (rotated or not) for each item."""
# Derived data (expanded to individual items).
data_widths = data['width'].to_numpy()
@@ -80,14 +87,10 @@ def solve_with_duplicate_items(data, height, width):
num_data_items = len(base_item_values)
# Create rotated items by duplicating.
item_widths = np.concatenate(
(base_item_widths, base_item_heights)).to_list()
item_heights = np.concatenate(
(base_item_heights, base_item_widths)).to_list()
item_widths = np.concatenate((base_item_widths, base_item_heights))
item_heights = np.concatenate((base_item_heights, base_item_widths))
item_values = np.concatenate((base_item_values, base_item_values))
# Scale values to become integers.
item_values = (item_values * 1000.0).astype('int').to_list()
num_items = len(item_values)
# OR-Tools model
@@ -95,41 +98,45 @@ def solve_with_duplicate_items(data, height, width):
# Variables
## u[i] : item i is used
is_used = [model.NewBoolVar(f'u{i}') for i in range(num_items)]
x_starts = []
x_ends = []
y_starts = []
y_ends = []
is_used = []
x_intervals = []
y_intervals = []
## x_start[i],y_start[i] : location of item i
x_start = [
model.NewIntVar(0, width, f'x_start{i}') for i in range(num_items)
]
y_start = [
model.NewIntVar(0, height, f'y_start{i}') for i in range(num_items)
]
for i in range(num_items):
## Is the item used?
is_used.append(model.NewBoolVar(f'is_used{i}'))
## x_end[i],y_end[i] : upper limit of interval variable
x_end = [model.NewIntVar(0, width, f'x_end{i}') for i in range(num_items)]
y_end = [model.NewIntVar(0, height, f'y_end{i}') for i in range(num_items)]
## Item coordinates.
x_starts.append(model.NewIntVar(0, max_width, f'x_start{i}'))
x_ends.append(model.NewIntVar(0, max_width, f'x_end{i}'))
y_starts.append(model.NewIntVar(0, max_height, f'y_start{i}'))
y_ends.append(model.NewIntVar(0, max_height, f'y_end{i}'))
## interval variables
x_intervals = [
model.NewIntervalVar(x_start[i], item_widths[i] * is_used[i], x_end[i],
f'xival{i}') for i in range(num_items)
]
y_intervals = [
model.NewIntervalVar(y_start[i], item_heights[i] * is_used[i], y_end[i],
f'yival{i}') for i in range(num_items)
]
# only one of non-rotated/rotated pair can be used
for i in range(num_data_items):
model.Add(is_used[i] + is_used[i + num_data_items] <= 1)
## Interval variables.
x_intervals.append(
model.NewIntervalVar(x_starts[i], item_widths[i] * is_used[i],
x_ends[i], f'x_interval{i}'))
y_intervals.append(
model.NewIntervalVar(y_starts[i], item_heights[i] * is_used[i],
y_ends[i], f'y_interval{i}'))
# Constraints.
## Only one of non-rotated/rotated pair can be used.
for i in range(num_data_items):
model.Add(is_used[i] + is_used[i + num_data_items] <= 1)
## 2D no overlap.
model.AddNoOverlap2D(x_intervals, y_intervals)
## Objective.
model.Maximize(sum([is_used[i] * item_values[i] for i in range(num_items)]))
model.Maximize(
sum(is_used[i] * scale_double(item_values[i])
for i in range(num_items)))
model.SetObjectiveScaling(1e-3)
# Output proto to file.
@@ -149,18 +156,18 @@ def solve_with_duplicate_items(data, height, width):
if status == cp_model.OPTIMAL:
used = {i for i in range(num_items) if solver.BooleanValue(is_used[i])}
data = pd.DataFrame({
'x_start': [solver.Value(x_start[i]) for i in used],
'y_start': [solver.Value(y_start[i]) for i in used],
'x_start': [solver.Value(x_starts[i]) for i in used],
'y_start': [solver.Value(y_starts[i]) for i in used],
'item_width': [item_widths[i] for i in used],
'item_height': [item_heights[i] for i in used],
'x_end': [solver.Value(x_end[i]) for i in used],
'y_end': [solver.Value(y_end[i]) for i in used],
'x_end': [solver.Value(x_ends[i]) for i in used],
'y_end': [solver.Value(y_ends[i]) for i in used],
'item_value': [item_values[i] for i in used]
})
print(data)
def solve_with_rotations(data, height, width):
def solve_with_rotations(data, max_height, max_width):
"""Solve the problem by rotating items."""
# Derived data (expanded to individual items).
data_widths = data['width'].to_numpy()
@@ -168,55 +175,51 @@ def solve_with_rotations(data, height, width):
data_availability = data['available'].to_numpy()
data_values = data['value'].to_numpy()
item_widths = np.repeat(data_widths, data_availability).astype('int')
item_heights = np.repeat(data_heights, data_availability).astype('int')
item_widths = np.repeat(data_widths, data_availability)
item_heights = np.repeat(data_heights, data_availability)
item_values = np.repeat(data_values, data_availability)
num_items = len(item_widths)
# Scale values to become integers.
item_values = (item_values * 1000.0).astype('int')
# OR-Tools model.
model = cp_model.CpModel()
# Variables.
x_starts = []
x_sizes = []
x_ends = []
y_starts = []
y_sizes = []
y_ends = []
x_intervals = []
y_intervals = []
## x_start[i],y_start[i] : location of item i.
x_start = [
model.NewIntVar(0, width, f'x_start{i}') for i in range(num_items)
]
y_start = [
model.NewIntVar(0, height, f'y_start{i}') for i in range(num_items)
]
for i in range(num_items):
# X coordinates.
x_starts.append(model.NewIntVar(0, max_width, f'x_start{i}'))
x_sizes.append(
model.NewIntVarFromDomain(
cp_model.Domain.FromValues(
[0, int(item_widths[i]),
int(item_heights[i])]), f'x_size{i}'))
x_ends.append(model.NewIntVar(0, max_width, f'x_end{i}'))
## x_size[i],y_size[i] : sizes of item i.
x_size = [
model.NewIntVarFromDomain(
cp_model.Domain.FromValues(
[0, int(item_widths[i]),
int(item_heights[i])]), f'x_size{i}') for i in range(num_items)
]
y_size = [
model.NewIntVarFromDomain(
cp_model.Domain.FromValues(
[0, int(item_widths[i]),
int(item_heights[i])]), f'y_size{i}') for i in range(num_items)
]
# Y coordinates.
y_starts.append(model.NewIntVar(0, max_height, f'y_start{i}'))
y_sizes.append(
model.NewIntVarFromDomain(
cp_model.Domain.FromValues(
[0, int(item_widths[i]),
int(item_heights[i])]), f'y_size{i}'))
y_ends.append(model.NewIntVar(0, max_height, f'y_end{i}'))
## x_end[i],y_end[i] : upper limit of interval variable.
x_end = [model.NewIntVar(0, width, f'x_end{i}') for i in range(num_items)]
y_end = [model.NewIntVar(0, height, f'y_end{i}') for i in range(num_items)]
## Interval variables
x_intervals = [
model.NewIntervalVar(x_start[i], x_size[i], x_end[i], f'x_intervals{i}')
for i in range(num_items)
]
y_intervals = [
model.NewIntervalVar(y_start[i], y_size[i], y_end[i], f'y_intervals{i}')
for i in range(num_items)
]
## Interval variables
x_intervals.append(
model.NewIntervalVar(x_starts[i], x_sizes[i], x_ends[i],
f'x_interval{i}'))
y_intervals.append(
model.NewIntervalVar(y_starts[i], y_sizes[i], y_ends[i],
f'y_interval{i}'))
is_used = []
@@ -231,15 +234,15 @@ def solve_with_rotations(data, height, width):
### Only one state can be chosen.
model.Add(not_selected + no_rotation + rotation == 1)
### Define height and width.
### Define max_height and width.
dim1 = int(item_widths[i])
dim2 = int(item_heights[i])
model.Add(x_size[i] == 0).OnlyEnforceIf(not_selected)
model.Add(y_size[i] == 0).OnlyEnforceIf(not_selected)
model.Add(x_size[i] == dim1).OnlyEnforceIf(no_rotation)
model.Add(y_size[i] == dim2).OnlyEnforceIf(no_rotation)
model.Add(x_size[i] == dim2).OnlyEnforceIf(rotation)
model.Add(y_size[i] == dim1).OnlyEnforceIf(rotation)
model.Add(x_sizes[i] == 0).OnlyEnforceIf(not_selected)
model.Add(y_sizes[i] == 0).OnlyEnforceIf(not_selected)
model.Add(x_sizes[i] == dim1).OnlyEnforceIf(no_rotation)
model.Add(y_sizes[i] == dim2).OnlyEnforceIf(no_rotation)
model.Add(x_sizes[i] == dim2).OnlyEnforceIf(rotation)
model.Add(y_sizes[i] == dim1).OnlyEnforceIf(rotation)
is_used.append(not_selected.Not())
@@ -247,7 +250,9 @@ def solve_with_rotations(data, height, width):
model.AddNoOverlap2D(x_intervals, y_intervals)
# Objective.
model.Maximize(sum(is_used[i] * item_values[i] for i in range(num_items)))
model.Maximize(
sum(is_used[i] * scale_double(item_values[i])
for i in range(num_items)))
model.SetObjectiveScaling(1e-3)
# Output proto to file.
@@ -267,12 +272,12 @@ def solve_with_rotations(data, height, width):
if status == cp_model.OPTIMAL:
used = {i for i in range(num_items) if solver.BooleanValue(is_used[i])}
data = pd.DataFrame({
'x_start': [solver.Value(x_start[i]) for i in used],
'y_start': [solver.Value(y_start[i]) for i in used],
'item_width': [solver.Value(x_size[i]) for i in used],
'item_height': [solver.Value(y_size[i]) for i in used],
'x_end': [solver.Value(x_end[i]) for i in used],
'y_end': [solver.Value(y_end[i]) for i in used],
'x_start': [solver.Value(x_starts[i]) for i in used],
'y_start': [solver.Value(y_starts[i]) for i in used],
'item_width': [solver.Value(x_sizes[i]) for i in used],
'item_height': [solver.Value(y_sizes[i]) for i in used],
'x_end': [solver.Value(x_ends[i]) for i in used],
'y_end': [solver.Value(y_ends[i]) for i in used],
'item_value': [item_values[i] for i in used]
})
print(data)
@@ -280,11 +285,11 @@ def solve_with_rotations(data, height, width):
def main(_):
"""Solve the problem with all models."""
data, height, width = build_data()
data, max_height, max_width = build_data()
if FLAGS.model == 'duplicate':
solve_with_duplicate_items(data, height, width)
solve_with_duplicate_items(data, max_height, max_width)
else:
solve_with_rotations(data, height, width)
solve_with_rotations(data, max_height, max_width)
if __name__ == '__main__':