A state-of-the-art solver for (geometrical) packing problems.
PackingSolver solves the following problem types:
| Problem types | Examples |
|---|---|
rectangleguillotine
|
 |
rectangle
|
 |
box
|
 |
boxstacks
|
 |
onedimensional
|
 |
irregular
|
 |
Python interface
Python bindings are available for every solver. Install them from PyPI (Python >= 3.12; a new release is published for each commit on master):
pip install packingsolver
Or build them from a local checkout with pip install ..
rectangleguillotine solver
import packingsolver.rectangleguillotine as psg
instance_builder = psg.InstanceBuilder()
instance_builder.set_objective(psg.Objective.BinPackingWithLeftovers)
instance_builder.add_bin_type(1000, 700, copies=5)
instance_builder.add_item_type(250, 200, copies=2)
instance_builder.add_item_type(150, 300, copies=2)
instance_builder.add_item_type(200, 150, copies=3)
instance = instance_builder.build()
parameters = psg.OptimizeParameters()
parameters.time_limit = 5
output = psg.optimize(instance, parameters)
psg.visualize(output.solution).show()
rectangle solver
import packingsolver.rectangle as psr
instance_builder = psr.InstanceBuilder()
instance_builder.set_objective(psr.Objective.BinPackingWithLeftovers)
instance_builder.add_bin_type(1000, 500, copies=10)
instance_builder.add_item_type(300, 200, copies=10)
instance_builder.add_item_type(250, 150, copies=10)
instance = instance_builder.build()
parameters = psr.OptimizeParameters()
parameters.time_limit = 5
output = psr.optimize(instance, parameters)
psr.visualize(output.solution).show()
box solver
import packingsolver.box as psb
instance_builder = psb.InstanceBuilder()
instance_builder.set_objective(psb.Objective.Knapsack)
instance_builder.add_bin_type(216, 173, 110)
instance_builder.add_item_type(108, 76, 30, copies=20)
instance_builder.add_item_type(110, 43, 25, copies=20)
instance_builder.add_item_type(92, 81, 55, copies=20)
instance = instance_builder.build()
parameters = psb.OptimizeParameters()
parameters.time_limit = 5
output = psb.optimize(instance, parameters)
psb.visualize(output.solution).show()
boxstacks solver
import packingsolver.boxstacks as psbs
instance_builder = psbs.InstanceBuilder()
instance_builder.set_objective(psbs.Objective.Knapsack)
instance_builder.add_bin_type(7500, 2400, 3000)
instance_builder.add_item_type(2500, 800, 750, stackability_id=0, copies=10)
instance_builder.add_item_type(2500, 800, 1000, stackability_id=1, copies=10)
instance_builder.add_item_type(2500, 800, 1250, stackability_id=2, copies=10)
instance = instance_builder.build()
parameters = psbs.OptimizeParameters()
parameters.time_limit = 5
output = psbs.optimize(instance, parameters)
psbs.visualize(output.solution).show()
onedimensional solver
import packingsolver.onedimensional as pso
instance_builder = pso.InstanceBuilder()
instance_builder.set_objective(pso.Objective.BinPacking)
instance_builder.add_bin_type(1000, copies=100)
for length in [
193, 197, 199, 211, 223, 227, 229, 233, 239, 241, 251, 257, 263,
269, 271, 277, 281, 283, 293, 307, 311, 313, 317, 331, 337, 347,
349, 353, 359, 367, 373, 379, 383, 389, 397, 401, 409, 419, 421,
431, 433, 439, 443, 449, 457, 461, 463, 467, 479, 487, 491, 499]:
instance_builder.add_item_type(length)
instance = instance_builder.build()
parameters = pso.OptimizeParameters()
parameters.time_limit = 5
output = pso.optimize(instance, parameters)
pso.visualize(output.solution).show()
irregular solver
import packingsolver.irregular as psi
bar = [(0, 0), (80, 0), (80, 20), (0, 20)]
square = [(0, 0), (40, 0), (40, 40), (0, 40)]
t_shape = [(0, 0), (60, 0), (60, 20), (40, 20), (40, 40), (20, 40), (20, 20), (0, 20)]
s_shape = [(20, 0), (60, 0), (60, 20), (40, 20), (40, 40), (0, 40), (0, 20), (20, 20)]
z_shape = [(0, 0), (40, 0), (40, 20), (60, 20), (60, 40), (20, 40), (20, 20), (0, 20)]
l_shape = [(0, 0), (40, 0), (40, 20), (20, 20), (20, 60), (0, 60)]
j_shape = [(0, 0), (40, 0), (40, 60), (20, 60), (20, 20), (0, 20)]
cross = [
(20, 0), (40, 0), (40, 20), (60, 20), (60, 40), (40, 40),
(40, 60), (20, 60), (20, 40), (0, 40), (0, 20), (20, 20)]
rotations = [(0, 0, False), (90, 90, False), (180, 180, False), (270, 270, False)]
instance_builder = psi.InstanceBuilder()
instance_builder.set_objective(psi.Objective.BinPacking)
instance_builder.add_bin_type(psi.build_rectangle(0, 180, 0, 160), copies=3)
instance_builder.add_item_type(psi.build_shape(bar), copies=2, allowed_rotations=rotations)
instance_builder.add_item_type(psi.build_shape(square), copies=2)
instance_builder.add_item_type(psi.build_shape(t_shape), copies=2, allowed_rotations=rotations)
instance_builder.add_item_type(psi.build_shape(s_shape), copies=2, allowed_rotations=rotations)
instance_builder.add_item_type(psi.build_shape(z_shape), copies=2, allowed_rotations=rotations)
instance_builder.add_item_type(psi.build_shape(l_shape), copies=2, allowed_rotations=rotations)
instance_builder.add_item_type(psi.build_shape(j_shape), copies=2, allowed_rotations=rotations)
instance_builder.add_item_type(psi.build_shape(cross), copies=3)
instance = instance_builder.build()
parameters = psi.OptimizeParameters()
parameters.time_limit = 5
output = psi.optimize(instance, parameters)
psi.visualize(output.solution).show()
Command-line interface
Compilation
cmake -S . -B build -DCMAKE_BUILD_TYPE=Release
cmake --build build --config Release --parallel && cmake --install build --config Release --prefix install
rectangleguillotine solver
Features:
- Objectives:
- Knapsack
- Open dimension X
- Open dimension Y
- Bin packing
- Bin packing with leftovers
- Variable-sized bin packing
- With or without item rotations
- Stacks (precedence constraints on the order in which items are extracted)
- Bins may contain defects
- Allow or forbid cutting through a defect
- Number of stages
- Two- and three-staged patterns
- Exact, non-exact, roadef2018 and homogenous
- First cut vertical, horizontal or any
- Unlimited-staged patterns
- Two- and three-staged patterns
- Trims
- Cut thickness
- Minimum distance between consecutive 1-cuts
- Maximum distance between consecutive 1-cuts
- Minimum distance between consecutive 2-cuts
- Maximum distance between consecutive 2-cuts
- Minimum distance between cuts
- Maximum number of consecutive 1-cuts
- Maximum number of consecutive 2-cuts
Example:
./install/bin/packingsolver_rectangleguillotine \
--verbosity-level 1 \
--items data/rectangle/alvarez2002/ATP35_items.csv \
--bins data/rectangle/alvarez2002/ATP35_bins.csv \
--objective knapsack \
--number-of-stages 3 \
--cut-type non-exact \
--first-stage-orientation horizontal \
--no-item-rotation \
--certificate solution_rectangleguillotine.csv \
--time-limit 1
=================================
PackingSolver
=================================
Problem type
------------
RectangleGuillotine
Instance
--------
Objective: Knapsack
Number of item types: 29
Number of items: 153
Number of bin types: 1
Number of bins: 1
Number of stacks: 29
Number of defects: 0
Number of stages: 3
Cut type: NonExact
First stage orientation: Horizontal
min1cut: 0
max1cut: -1
min2cut: 0
max2cut: -1
Minimum waste: 1
one2cut: 0
Cut through defects: 0
Cut thickness: 0
Time Profit # items Comment
---- ------ ------- -------
0.001 68970 1 TS g 5 d Horizontal q 1
0.002 72000 1 TS g 5 d Horizontal q 1
0.009 140970 2 TS g 5 d Horizontal q 1
0.010 144000 2 TS g 5 d Horizontal q 1
0.011 212970 3 TS g 5 d Horizontal q 1
0.012 216000 3 TS g 5 d Horizontal q 1
0.013 284970 4 TS g 5 d Horizontal q 1
0.014 292395 5 TS g 5 d Horizontal q 1
0.015 306705 5 TS g 5 d Horizontal q 1
0.016 348839 5 TS g 5 d Horizontal q 1
0.017 358042 6 TS g 5 d Horizontal q 1
0.018 372343 6 TS g 5 d Horizontal q 1
0.019 379768 7 TS g 5 d Horizontal q 1
0.020 388389 7 TS g 5 d Horizontal q 1
0.021 408379 7 TS g 5 d Horizontal q 1
0.022 415804 8 TS g 5 d Horizontal q 1
0.023 424425 8 TS g 5 d Horizontal q 1
0.024 444415 8 TS g 5 d Horizontal q 1
0.025 451840 9 TS g 5 d Horizontal q 1
0.026 460461 9 TS g 5 d Horizontal q 1
0.027 480451 9 TS g 5 d Horizontal q 1
0.029 496497 10 TS g 5 d Horizontal q 1
0.030 502186 10 TS g 5 d Horizontal q 1
0.031 523921 11 TS g 5 d Horizontal q 1
0.032 539967 12 TS g 5 d Horizontal q 1
0.033 547003 9 TS g 5 d Horizontal q 2
0.034 561304 9 TS g 5 d Horizontal q 2
0.035 581548 9 TS g 5 d Horizontal q 2
0.036 588973 10 TS g 5 d Horizontal q 2
0.036 597058 10 TS g 5 d Horizontal q 2
0.037 599368 11 TS g 5 d Horizontal q 2
0.039 602118 14 TS g 4 d Horizontal q 2
0.043 605793 11 TS g 5 d Horizontal q 9
0.049 606147 13 TS g 5 d Horizontal q 19
0.059 606672 12 TS g 5 d Horizontal q 42
0.074 607062 14 TS g 5 d Horizontal q 94
0.104 609550 15 TS g 5 d Horizontal q 211
0.154 610101 31 TS g 4 d Horizontal q 141
0.155 610578 31 TS g 4 d Horizontal q 141
0.156 610787 32 TS g 4 d Horizontal q 141
0.212 611135 34 TS g 4 d Horizontal q 211
0.294 614725 31 TS g 4 d Horizontal q 316
0.304 614967 42 TS g 4 d Horizontal q 316
0.453 616880 16 TS g 5 d Horizontal q 1139
0.874 619897 28 TS g 4 d Horizontal q 1066
Final statistics
----------------
Time (s): 1.0037
Solution
--------
Number of items: 28 / 153 (18.3007%)
Item area: 619897 / 4322082 (14.3426%)
Item profit: 619897 / 4.32208e+06 (14.3426%)
Number of bins: 1 / 1 (100%)
Bin cost: 623040
Waste: 3143
Waste (%): 0.504462
Full waste: 3143
Full waste (%): 0.504462
Visualize solution:
python3 scripts/visualize_rectangleguillotine.py solution_rectangleguillotine.csv
rectangle solver
Features:
- Objectives:
- Knapsack
- Open dimension X
- Open dimension Y
- Bin packing
- Bin packing with leftovers
- Variable-sized bin packing
- With or without item rotations
- Bins may contain defects
- Maximum weight in bins
- Unloading constraints: only horizontal/vertical movements, increasing x/y
Example:
./install/bin/packingsolver_rectangle \
--verbosity-level 1 \
--items data/rectangle/afsharian2014/450-200.txt/C22M25R10N15_D4_items.csv \
--bins data/rectangle/afsharian2014/450-200.txt/C22M25R10N15_D4_bins.csv \
--defects data/rectangle/afsharian2014/450-200.txt/C22M25R10N15_D4_defects.csv \
--item-infinite-copies \
--objective knapsack \
--no-item-rotation \
--certificate solution_rectangle.csv \
--time-limit 5
=================================
PackingSolver
=================================
Problem type
------------
Rectangle
Instance
--------
Objective: Knapsack
Number of item types: 25
Number of items: 247
Number of bin types: 1
Number of bins: 1
Number of groups: 1
Number of defects: 4
Unloading constraint: None
Total item area: 2576510
Total item width: 33005
Total item height: 17382
Smallest item width: 47
Smallest item height: 21
Total bin area: 90000
Total item weight: 0
Total bin weight: 0
Time Profit # items Comment
---- ------ ------- -------
0.001 10773 1 TS g 4 d X q 1
0.002 17052 1 TS g 4 d X q 1
0.002 23765 1 TS g 4 d X q 1
0.003 27825 2 TS g 4 d X q 1
0.003 30429 2 TS g 4 d X q 1
0.004 34538 2 TS g 4 d Y q 1
0.004 39178 3 TS g 4 d Y q 1
0.005 40237 4 TS g 4 d X q 1
0.005 43421 2 TS g 5 d Y q 1
0.006 43818 4 TS g 4 d Y q 1
0.006 50405 5 TS g 4 d X q 1
0.007 52631 6 TS g 4 d X q 1
0.007 53985 5 TS g 5 d Y q 1
0.008 54875 7 TS g 4 d X q 1
0.008 57101 8 TS g 4 d X q 1
0.009 59327 9 TS g 4 d X q 1
0.009 61553 10 TS g 4 d X q 1
0.010 63797 11 TS g 4 d X q 1
0.010 66041 12 TS g 4 d X q 1
0.011 66125 13 TS g 4 d X q 1
0.011 67227 15 TS g 4 d X q 1
0.012 69471 16 TS g 4 d X q 1
0.014 69760 17 TS g 4 d X q 3
0.017 70866 10 TS g 5 d Y q 19
0.017 71638 11 TS g 5 d Y q 19
0.020 71674 12 TS g 5 d Y q 28
0.050 72296 11 TS g 5 d Y q 141
0.162 72704 21 TS g 4 d X q 141
0.282 72832 19 TS g 4 d Y q 316
0.282 73344 19 TS g 4 d Y q 316
0.286 73443 20 TS g 4 d Y q 316
0.813 73980 20 TS g 4 d X q 711
1.196 73997 22 TS g 4 d X q 1066
1.794 74170 21 TS g 4 d X q 1599
4.873 74986 22 TS g 4 d X q 3597
Final statistics
----------------
Time (s): 5.02934
Solution
--------
Number of items: 22 / 247 (8.90688%)
Item area: 74986 / 2576510 (2.91037%)
Item weight: 0 / 0 (-nan%)
Item profit: 74986 / 2.57651e+06 (2.91037%)
Number of bins: 1 / 1 (100%)
Bin area: 90000 / 90000 (100%)
Bin weight: 0 / 0 (-nan%)
Bin cost: 90000
Waste: 14166
Waste (%): 15.8897
Full waste: 15014
Full waste (%): 16.6822
Area load: 0.833178
Weight load: -nan
X max: 448
Y max: 199
Leftover value: 848
Visualize solution:
python3 scripts/visualize_rectangle.py solution_rectangle.csv
box solver
Features:
- Objectives:
- Knapsack
- Bin packing
- Open dimension X
- Open dimension Y
- Open dimension Z
- Variable-sized bin packing
- Select allowed item rotations (among the 6 possible rotations)
- Maximum weight in bins
Example:
./install/bin/packingsolver_box \
--verbosity-level 1 \
--items ./data/box/bischoff1995/BR3.txt_1 \
--objective knapsack \
--certificate solution_box.csv \
--output output.json \
--time-limit 10
=================================
PackingSolver
=================================
Problem type
------------
Box
Instance
--------
Objective: Knapsack
Number of item types: 8
Number of items: 94
Number of bin types: 1
Number of bins: 1
Number of defects: 0
Total item volume: 29989656
Total item profit: 2.99897e+07
Largest item profit: 867240
Total item weight: 0
Largest item copies: 24
Total bin volume: 30089620
Total bin weight: inf
Largest bin cost: 136771
Time Profit # items Comment
---- ------ ------- -------
0.000 246240 1 TS g 4 d Y q 1
0.001 409860 1 TS g 4 d Y q 1
0.008 867240 1 TS g 4 d Y q 1
0.008 1.11348e+06 2 TS g 4 d Y q 1
0.008 1.2771e+06 2 TS g 5 d Y q 1
0.008 1.73448e+06 2 TS g 5 d Y q 1
0.008 1.98072e+06 3 TS g 5 d Y q 1
0.009 2.14434e+06 3 TS g 5 d Y q 1
0.009 2.60172e+06 3 TS g 5 d Y q 1
0.009 2.84796e+06 4 TS g 5 d Y q 1
0.009 3.01158e+06 4 TS g 5 d Y q 1
0.009 3.46896e+06 4 TS g 5 d Y q 1
0.010 3.7152e+06 5 TS g 5 d X q 1
0.010 3.87882e+06 5 TS g 5 d X q 1
0.010 4.3362e+06 5 TS g 5 d X q 1
0.011 4.58244e+06 6 TS g 5 d X q 1
0.011 4.74606e+06 6 TS g 5 d X q 1
0.011 5.20344e+06 6 TS g 5 d X q 1
0.011 5.44968e+06 7 TS g 5 d X q 1
0.011 5.6133e+06 7 TS g 5 d X q 1
0.012 6.07068e+06 7 TS g 5 d X q 1
0.012 6.18893e+06 8 TS g 5 d X q 1
0.012 6.31692e+06 8 TS g 5 d Y q 1
0.013 6.48054e+06 8 TS g 5 d Y q 1
0.013 6.93792e+06 8 TS g 5 d Y q 1
0.013 7.05617e+06 9 TS g 5 d X q 1
0.013 7.18416e+06 9 TS g 5 d Y q 1
0.014 7.34778e+06 9 TS g 5 d Y q 1
0.014 7.80516e+06 9 TS g 5 d Y q 1
0.014 7.92341e+06 10 TS g 5 d X q 1
0.015 8.0514e+06 10 TS g 5 d Y q 1
0.015 8.21502e+06 10 TS g 5 d Y q 1
0.015 8.6724e+06 10 TS g 5 d Y q 1
0.015 8.79065e+06 11 TS g 5 d X q 1
0.016 8.91864e+06 11 TS g 5 d Y q 1
0.016 9.08226e+06 11 TS g 5 d Y q 1
0.016 9.53964e+06 11 TS g 5 d Y q 1
0.017 9.65789e+06 12 TS g 5 d X q 1
0.017 9.78588e+06 12 TS g 5 d Y q 1
0.017 9.9495e+06 12 TS g 5 d Y q 1
0.018 1.00678e+07 13 TS g 5 d X q 1
0.018 1.01957e+07 13 TS g 5 d Y q 1
0.018 1.03594e+07 13 TS g 5 d Y q 1
0.019 1.04776e+07 14 TS g 5 d X q 1
0.019 1.06056e+07 14 TS g 5 d Y q 1
0.019 1.07692e+07 14 TS g 5 d Y q 1
0.020 1.08506e+07 15 TS g 5 d X q 1
0.020 1.10155e+07 15 TS g 5 d Y q 1
0.021 1.11791e+07 15 TS g 5 d Y q 1
0.021 1.12151e+07 17 TS g 5 d X q 1
0.021 1.14253e+07 16 TS g 5 d Y q 1
0.022 1.15889e+07 16 TS g 5 d Y q 1
0.022 1.17516e+07 18 TS g 5 d X q 1
0.023 1.18352e+07 17 TS g 5 d Y q 1
0.023 1.19988e+07 17 TS g 5 d Y q 1
0.024 1.21615e+07 19 TS g 5 d X q 1
0.024 1.24077e+07 20 TS g 5 d X q 1
0.025 1.25714e+07 20 TS g 5 d X q 1
0.025 1.28176e+07 21 TS g 5 d X q 1
0.026 1.29812e+07 21 TS g 5 d X q 1
0.026 1.32275e+07 22 TS g 5 d X q 1
0.027 1.33911e+07 22 TS g 5 d X q 1
0.027 1.36373e+07 23 TS g 5 d X q 1
0.028 1.38009e+07 23 TS g 5 d X q 1
0.028 1.40472e+07 24 TS g 5 d X q 1
0.029 1.41739e+07 24 TS g 5 d X q 1
0.030 1.44201e+07 25 TS g 5 d X q 1
0.030 1.45469e+07 25 TS g 5 d X q 1
0.031 1.47931e+07 26 TS g 5 d X q 1
0.031 1.49198e+07 26 TS g 5 d X q 1
0.032 1.51661e+07 27 TS g 5 d X q 1
0.032 1.52928e+07 27 TS g 5 d X q 1
0.033 1.54123e+07 28 TS g 5 d X q 1
0.033 1.5539e+07 28 TS g 5 d X q 1
0.034 1.56657e+07 28 TS g 5 d Y q 1
0.035 1.57853e+07 29 TS g 5 d X q 1
0.035 1.5912e+07 29 TS g 5 d X q 1
0.036 1.60387e+07 29 TS g 5 d Y q 1
0.036 1.61582e+07 30 TS g 5 d X q 1
0.037 1.62849e+07 30 TS g 5 d X q 1
0.037 1.64117e+07 30 TS g 5 d Y q 1
0.038 1.65312e+07 31 TS g 5 d X q 1
0.039 1.66579e+07 31 TS g 5 d X q 1
0.039 1.67846e+07 31 TS g 5 d Y q 1
0.040 1.69041e+07 32 TS g 5 d X q 1
0.040 1.70309e+07 32 TS g 5 d X q 1
0.041 1.71092e+07 32 TS g 5 d Y q 1
0.042 1.72771e+07 33 TS g 5 d X q 1
0.042 1.73554e+07 33 TS g 5 d X q 1
0.043 1.74338e+07 33 TS g 5 d Y q 1
0.043 1.76017e+07 34 TS g 5 d X q 1
0.044 1.768e+07 34 TS g 5 d X q 1
0.045 1.77583e+07 34 TS g 5 d Y q 1
0.045 1.79263e+07 35 TS g 5 d X q 1
0.046 1.80046e+07 35 TS g 5 d X q 1
0.047 1.80829e+07 35 TS g 5 d Y q 1
0.047 1.81725e+07 36 TS g 5 d X q 1
0.048 1.82508e+07 36 TS g 5 d X q 1
0.049 1.84075e+07 36 TS g 5 d Y q 1
0.049 1.84971e+07 37 TS g 5 d X q 1
0.050 1.85754e+07 37 TS g 5 d X q 1
0.051 1.87321e+07 37 TS g 5 d Y q 1
0.051 1.88216e+07 38 TS g 5 d X q 1
0.052 1.89e+07 38 TS g 5 d X q 1
0.053 1.90567e+07 38 TS g 5 d Y q 1
0.053 1.91462e+07 39 TS g 5 d X q 1
0.054 1.92246e+07 39 TS g 5 d X q 1
0.055 1.93812e+07 39 TS g 5 d Y q 1
0.056 1.94708e+07 40 TS g 5 d X q 1
0.056 1.95491e+07 40 TS g 5 d X q 1
0.057 1.97058e+07 40 TS g 5 d Y q 1
0.058 1.97954e+07 41 TS g 5 d X q 1
0.059 1.98737e+07 41 TS g 5 d X q 1
0.059 1.9952e+07 41 TS g 5 d Y q 1
0.060 2.00416e+07 42 TS g 5 d X q 1
0.061 2.01199e+07 42 TS g 5 d X q 1
0.062 2.01599e+07 43 TS g 5 d X q 1
0.063 2.01885e+07 43 TS g 5 d Y q 1
0.063 2.02382e+07 43 TS g 5 d X q 1
0.064 2.03068e+07 44 TS g 5 d Y q 1
0.065 2.0313e+07 44 TS g 5 d X q 1
0.066 2.03816e+07 45 TS g 5 d Y q 1
0.067 2.05593e+07 45 TS g 5 d X q 1
0.067 2.06376e+07 45 TS g 5 d X q 1
0.069 2.08055e+07 46 TS g 5 d X q 1
0.069 2.08839e+07 46 TS g 5 d X q 1
0.070 2.10021e+07 47 TS g 5 d X q 1
0.071 2.12084e+07 47 TS g 5 d X q 1
0.072 2.13267e+07 48 TS g 5 d X q 1
0.073 2.1533e+07 48 TS g 5 d X q 1
0.074 2.16513e+07 49 TS g 5 d X q 1
0.075 2.18576e+07 49 TS g 5 d X q 1
0.076 2.19758e+07 50 TS g 5 d X q 1
0.077 2.21038e+07 50 TS g 5 d X q 1
0.078 2.22221e+07 51 TS g 5 d X q 1
0.079 2.23501e+07 51 TS g 5 d X q 1
0.080 2.24683e+07 52 TS g 5 d X q 1
0.081 2.25444e+07 52 TS g 5 d X q 1
0.081 2.25963e+07 52 TS g 5 d X q 1
0.083 2.27146e+07 53 TS g 5 d X q 1
0.083 2.27907e+07 53 TS g 5 d X q 1
0.084 2.28425e+07 53 TS g 5 d X q 1
0.085 2.29608e+07 54 TS g 5 d X q 1
0.086 2.29961e+07 70 TS g 4 d X q 1
0.087 2.31228e+07 70 TS g 4 d X q 1
0.088 2.3369e+07 71 TS g 4 d X q 1
0.089 2.34958e+07 71 TS g 4 d X q 1
0.091 2.3742e+07 72 TS g 4 d X q 1
0.092 2.38687e+07 72 TS g 4 d X q 1
0.093 2.42417e+07 73 TS g 4 d X q 1
0.094 2.44879e+07 74 TS g 4 d X q 1
0.095 2.45662e+07 74 TS g 4 d X q 1
0.096 2.48125e+07 75 TS g 4 d X q 1
0.100 2.48619e+07 66 TS g 5 d X q 1
0.101 2.49802e+07 67 TS g 5 d X q 1
0.103 2.50984e+07 68 TS g 5 d X q 1
0.104 2.51733e+07 69 TS g 5 d X q 1
0.105 2.52481e+07 70 TS g 5 d X q 1
0.106 2.53229e+07 71 TS g 5 d X q 1
0.107 2.53978e+07 72 TS g 5 d X q 1
0.158 2.54632e+07 79 TS g 4 d X q 2
0.255 2.56576e+07 80 TS g 4 d X q 3
0.399 2.5706e+07 80 TS g 4 d X q 4
0.956 2.57613e+07 73 TS g 5 d X q 9
0.970 2.58362e+07 74 TS g 5 d X q 9
1.625 2.59038e+07 74 TS g 5 d X q 13
1.641 2.59787e+07 75 TS g 5 d X q 13
2.772 2.59929e+07 80 TS g 4 d X q 19
2.921 2.59991e+07 74 TS g 5 d X q 19
2.953 2.60305e+07 75 TS g 5 d X q 19
2.954 2.60739e+07 75 TS g 5 d X q 19
2.993 2.61488e+07 76 TS g 5 d X q 19
7.892 2.62568e+07 80 TS g 4 d X q 42
7.901 2.63086e+07 80 TS g 4 d X q 42
7.932 2.63209e+07 81 TS g 4 d X q 42
7.936 2.63728e+07 81 TS g 4 d X q 42
7.954 2.65153e+07 82 TS g 4 d X q 42
7.956 2.65188e+07 82 TS g 4 d X q 42
7.958 2.65672e+07 82 TS g 4 d X q 42
7.972 2.67132e+07 83 TS g 4 d X q 42
Final statistics
----------------
Time (s): 10.0127
Solution
--------
Number of items: 83 / 94 (88.2979%)
Item volume: 2.67132e+07 / 2.99897e+07 (89.0746%)
Item weight: 0 / 0 (-nan%)
Item profit: 2.67132e+07 / 2.99897e+07 (89.0746%)
Number of stacks: 0
Stack area: 0
Number of bins: 1 / 1 (100%)
Bin volume: 30089620 / 30089620 (100%)
Bin area: 136771 / 136771 (100%)
Bin weight: inf / inf (-nan%)
Bin cost: 136771
Waste: 3325190
Waste (%): 11.0698
Full waste: 3376450
Full waste (%): 11.2213
Volume load: 0.887787
Area load: 0
Weight load: 0
X max: 586
Y max: 233
Visualize solution:
python3 scripts/visualize_box.py solution_box.csv
boxstacks solver
Features:
- Objectives:
- Knapsack
- Bin packing
- Variable-sized bin packing
- Select allowed item rotations (among the 6 possible rotations)
- Nesting height when stacking items
- Maximum number of items in a stack containing an item of a given type
- Maximum weight allowed above an item of a given type
- Maximum weight in bins
- Maximum stack density
- Maximum weight on middle and rear axles
- Unloading constraints: only horizontal/vertical movements, increasing x/y
Example:
python3 scripts/download_data.py --data roadef2022_2024-04-25_bpp
./install/bin/packingsolver_boxstacks \
--verbosity-level 1 \
--items data/boxstacks/roadef2022_2024-04-25_bpp/C/AS/AS_149_items.csv \
--bins data/boxstacks/roadef2022_2024-04-25_bpp/C/AS/AS_149_bins.csv \
--parameters data/boxstacks/roadef2022_2024-04-25_bpp/C/AS/AS_149_parameters.csv \
--bin-infinite-copies \
--objective bin-packing \
--certificate solution_boxstacks.csv \
--time-limit 1
=================================
PackingSolver
=================================
Problem type
------------
BoxStacks
Instance
--------
Objective: BinPacking
Number of item types: 13
Number of items: 118
Number of bin types: 1
Number of bins: 118
Number of groups: 1
Number of defects: 0
Unloading constraint: IncreasingX
Item volume: 196704000000
Bin volume: 13001535000000
Item weight: 17323.9
Bin weight: 2.832e+06
Time Bins Full waste (%) Comment
---- ---- -------------- -------
0.119 2 10.74 iteration 0
Final statistics
----------------
Time (s): 0.119291
Solution
--------
Number of items: 118 / 118 (100%)
Item volume: 1.96704e+11 / 1.96704e+11 (100%)
Item weight: 17323.9 / 17323.9 (100%)
Item profit: 1.96704e+11 / 1.96704e+11 (100%)
Number of stacks: 37
Stack area: 69600000
Number of bins: 2 / 118 (1.69492%)
Bin volume: 220365000000 / 13001535000000 (1.69492%)
Bin area: 74700000 / 4407300000 (1.69492%)
Bin weight: 48000 / 2832000 (1.69492%)
Bin cost: 6
Waste: 19678500000
Waste (%): 9.09431
Full waste: 23661000000
Full waste (%): 10.7372
Volume load: 0.0151293
Area load: 0.015792
Weight load: 0.00611719
X max: 14400
Y max: 2400
Visualize solution:
python3 scripts/visualize_boxstacks.py solution_boxstacks.csv
onedimensional solver
Features:
- Objectives:
- Knapsack
- Bin packing
- Bin packing with leftovers
- Variable-sized bin packing
- Nesting length between consecutive items
- Maximum number of items in a bin containing an item of a given type
- Maximum weight allowed after an item of a given type
- Maximum weight in bins
- Item type / bin type eligibility
Example:
./install/bin/packingsolver_onedimensional \
--verbosity-level 2 \
--items data/onedimensional/users/2024-04-21_items.csv \
--bins data/onedimensional/users/2024-04-21_bins.csv \
--parameters data/onedimensional/users/2024-04-21_parameters.csv \
--time-limit 1 \
--certificate solution_onedimensional.csv
=================================
PackingSolver
=================================
Problem type
------------
OneDimensional
Instance
--------
Objective: VariableSizedBinPacking
Number of item types: 7
Number of items: 43554
Number of bin types: 1
Number of bins: 43554
Bin type Length Max wght Cost Copies Copies min
-------- ------ -------- ---- ------ ----------
0 6000 inf 6000 43554 0
Bin type Eligibility
-------- -----------
Item type Length Weight MaxWgtAft MaxStck Profit Copies Eligibility
--------- ------ ------ --------- ------- ------ ------ -----------
0 837 0 inf 2147483647 837 820 -1
1 1587 0 inf 2147483647 1587 26640 -1
2 1987 0 inf 2147483647 1987 372 -1
3 2487 0 inf 2147483647 2487 15602 -1
4 727 0 inf 2147483647 727 40 -1
5 1627 0 inf 2147483647 1627 40 -1
6 747 0 inf 2147483647 747 40 -1
Time Cost # bins Full waste (%) Comment
---- ---- ------ -------------- -------
0.006 8.8338e+07 14723 6.46 SVC it 0
0.011 8.769e+07 14615 5.77 SVC it 1
0.023 8.7624e+07 14604 5.70 SVC it 3
0.027 8.7612e+07 14602 5.69 SVC it 4
0.070 8.757e+07 14595 5.64 CG n 1
Final statistics
----------------
Time (s): 1.00035
Solution
--------
Number of items: 43554 / 43554 (100%)
Item length: 8.26294e+07 / 8.26294e+07 (100%)
Item profit: 8.26294e+07 / 8.26294e+07 (100%)
Number of bins: 14595 / 43554 (33.5101%)
Bin length: 87570000 / 261324000 (33.5101%)
Bin cost: 8.757e+07
Waste: 4940351
Waste (%): 5.64162
Full waste: 4940602
Full waste (%): 5.64189
Bin Type Copies Length Weight # items
--- ---- ------ ------ ------ -------
0 0 124 5969 0 3
1 0 231 4978 0 2
2 0 13320 5669 0 3
3 0 820 5819 0 3
4 0 40 5709 0 3
5 0 40 5729 0 3
6 0 20 5749 0 3
Visualize:
python3 scripts/visualize_onedimensional.py solution_onedimensional.csv
irregular solver
Features:
- Objectives:
- Knapsack
- Open dimension X
- Open dimension Y
- Bin packing
- Bin packing with leftovers
- Variable-sized bin packing
- Non-convex shapes (for items or bins)
- Shapes with holes
- Discrete and continuous rotations of items
- Mirroring of items
- Bins may contain different quality areas
- Minimum distance between the bin and the items
- Minimum distance between each pair of items
Example:
./install/bin/packingsolver_irregular \
--verbosity-level 1 \
--input ./data/irregular/opencutlist/knight_armor.json \
--time-limit 10 \
--certificate solution_irregular.json
=================================
PackingSolver
=================================
Problem type
------------
Irregular
Instance
--------
Objective: BinPackingWithLeftovers
Number of item types: 45
Number of items: 100
Number of bin types: 1
Number of bins: 1
Number of defects: 0
Number of rectangular items: 5
Number of circular items: 0
Item area: 2.91022e+06
Smallest item area: 3749.55
Largest item area: 90886.6
Bin area: 5.796e+06
Item-bin minimum spacing: 0
Item-item minimum spacing: 0
Time # bins Leftover Comment
---- ------ -------- -------
0.365 1 1.55619e+06 TS g 0 d 5 q 1
0.367 1 1.64045e+06 TS g 0 d 5 q 1
0.413 1 1.79437e+06 TS g 0 d 0 q 1
0.451 1 1.81666e+06 TS g 0 d 4 q 1
0.520 1 1.98572e+06 TS g 1 d 5 q 1
0.543 1 2.03254e+06 TS g 1 d 4 q 1
2.266 1 2.05049e+06 TS g 1 d 5 q 3
3.159 1 2.05693e+06 TS g 1 d 0 q 4
3.544 1 2.06829e+06 TS g 1 d 1 q 4
4.708 1 2.11687e+06 TS g 1 d 0 q 6
5.137 1 2.12846e+06 TS g 1 d 1 q 6
Final statistics
----------------
Time (s): 10.0096
Solution
--------
Number of items: 100 / 100 (100%)
Item area: 2.91016e+06 / 2.91022e+06 (99.9981%)
Item profit: 2.91022e+06 / 2.91022e+06 (100%)
Number of bins: 1 / 1 (100%)
Bin area: 5796000 / 5796000 (100%)
Bin cost: 5.796e+06
Full waste: 2885838
Full waste (%): 49.7902
X max: 1771.76
Y max: 2070
Leftover value: 2.12846e+06
Visualize:
python3 scripts/visualize_irregular.py solution_irregular.json
1 maintainer
Metadata
1 maintainer
Release files for packingsolver 0.1.1056
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| packingsolver-0.1.1056.tar.gz | 819.9 kB | Details |
Built distributions (wheels)
| File | Reset | |||
|---|---|---|---|---|
| packingsolver-0.1.1056-cp312-abi3-win_amd64.whl | CPython 3.12 | abi3 | Windows x86-64 | Details |
| packingsolver-0.1.1056-cp312-abi3-win32.whl | CPython 3.12 | abi3 | Windows x86-32 | Details |
| packingsolver-0.1.1056-cp312-abi3-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl | CPython 3.12 | abi3 | Linux glibc 2.27+ x86-64, Linux glibc 2.28+ x86-64 | Details |
| packingsolver-0.1.1056-cp312-abi3-manylinux_2_26_aarch64.manylinux_2_28_aarch64.whl | CPython 3.12 | abi3 | Linux glibc 2.26+ ARM64, Linux glibc 2.28+ ARM64 | Details |
| packingsolver-0.1.1056-cp312-abi3-macosx_11_0_x86_64.whl | CPython 3.12 | abi3 | macOS 11.0+ x86-64 | Details |
| packingsolver-0.1.1056-cp312-abi3-macosx_11_0_arm64.whl | CPython 3.12 | abi3 | macOS 11.0+ ARM64 | Details |
Total release size: 28.5 MB
Release files / packingsolver-0.1.1056.tar.gz
| Download URL | packingsolver-0.1.1056.tar.gz |
|---|---|
| Size | 819.9 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
7a449448905330cd32db07d2fb8f4d0567cb687029ae0a4908b2fcbc1cff2abc
|
|
BLAKE2b-256 checksum How to use checksums |
b1fc9d485b72fba17ea40d0569f95118012a28ef2b624f2c912850f271b76060
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 3, 2026.
Transparency logRelease files / packingsolver-0.1.1056-cp312-abi3-win_amd64.whl
| Download URL | packingsolver-0.1.1056-cp312-abi3-win_amd64.whl |
|---|---|
| Size | 4.0 MB |
| Tags | CPython 3.12 Windows x86-64 abi3 |
|
SHA-256 checksum How to use checksums |
6e0e4e2d74e76397559036ea72264279533d9ed39afbe7ff057901418f0c03a4
|
|
BLAKE2b-256 checksum How to use checksums |
abe0617c8befd94cd9fafc6a30f2baf861ace0c462435c95d36a0dd76c9535e7
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 3, 2026.
Transparency logRelease files / packingsolver-0.1.1056-cp312-abi3-win32.whl
| Download URL | packingsolver-0.1.1056-cp312-abi3-win32.whl |
|---|---|
| Size | 3.6 MB |
| Tags | CPython 3.12 Windows x86-32 abi3 |
|
SHA-256 checksum How to use checksums |
b02cbc266cf215deadc732219b4953eb505225f37bff89bb891240e2b837beb7
|
|
BLAKE2b-256 checksum How to use checksums |
453539a2610ae1740f66707734a3a91623827fad35f04b4237f72c04454913ed
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 3, 2026.
Transparency logRelease files / packingsolver-0.1.1056-cp312-abi3-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
| Download URL | packingsolver-0.1.1056-cp312-abi3-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl |
|---|---|
| Size | 5.8 MB |
| Tags | CPython 3.12 Linux glibc 2.27+ x86-64 Linux glibc 2.28+ x86-64 abi3 |
|
SHA-256 checksum How to use checksums |
63fd0fb8a546563a8b16b395dae2f816cb3dfe6e2b854bb7e50ef8ab48d38bf9
|
|
BLAKE2b-256 checksum How to use checksums |
c14cca7c8a16ecfe2365734b90473e1ae843ff58c75c179290029d1b51588782
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 3, 2026.
Transparency logRelease files / packingsolver-0.1.1056-cp312-abi3-manylinux_2_26_aarch64.manylinux_2_28_aarch64.whl
| Download URL | packingsolver-0.1.1056-cp312-abi3-manylinux_2_26_aarch64.manylinux_2_28_aarch64.whl |
|---|---|
| Size | 5.3 MB |
| Tags | CPython 3.12 Linux glibc 2.26+ ARM64 Linux glibc 2.28+ ARM64 abi3 |
|
SHA-256 checksum How to use checksums |
2341e21677eca7fa0c8c18ad9c10ebb03ecae85ed02fe17f72e8e2a13719d0f6
|
|
BLAKE2b-256 checksum How to use checksums |
2f2bf47e6211e89200ba2f4d40010e7d187940fb5824302ea196940723423565
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 3, 2026.
Transparency logRelease files / packingsolver-0.1.1056-cp312-abi3-macosx_11_0_x86_64.whl
| Download URL | packingsolver-0.1.1056-cp312-abi3-macosx_11_0_x86_64.whl |
|---|---|
| Size | 4.8 MB |
| Tags | CPython 3.12 abi3 macOS 11.0+ x86-64 |
|
SHA-256 checksum How to use checksums |
25cc39c76990f6667d0d02fb206a04b2248f8c397c592293c7775421c77d86d6
|
|
BLAKE2b-256 checksum How to use checksums |
c820c63930218457325aa3b6945bb1e37ddecfc9a906dbd02b29bde5b961bea6
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 3, 2026.
Transparency logRelease files / packingsolver-0.1.1056-cp312-abi3-macosx_11_0_arm64.whl
| Download URL | packingsolver-0.1.1056-cp312-abi3-macosx_11_0_arm64.whl |
|---|---|
| Size | 4.2 MB |
| Tags | CPython 3.12 abi3 macOS 11.0+ ARM64 |
|
SHA-256 checksum How to use checksums |
63c3458da7bf68571971f80cd21f8dab7f04370f2cfc864e2ff99b6392c81d3e
|
|
BLAKE2b-256 checksum How to use checksums |
e1d919dddcc8dc1036a112cabd354371a9af32d182eae11a2734e0c05cab0208
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 3, 2026.
Transparency log
