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 0.1.1064
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Source distribution (sdist)
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| packingsolver-0.1.1064.tar.gz | 821.9 kB | Details |
Built distributions (wheels)
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| packingsolver-0.1.1064-cp312-abi3-win_amd64.whl | CPython 3.12 | abi3 | Windows x86-64 | Details |
| packingsolver-0.1.1064-cp312-abi3-win32.whl | CPython 3.12 | abi3 | Windows x86-32 | Details |
| packingsolver-0.1.1064-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-0.1.1064-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-0.1.1064-cp312-abi3-macosx_11_0_x86_64.whl | CPython 3.12 | abi3 | macOS 11.0+ x86-64 | Details |
| packingsolver-0.1.1064-cp312-abi3-macosx_11_0_arm64.whl | CPython 3.12 | abi3 | macOS 11.0+ ARM64 | Details |
Total release size: 28.5 MB
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