Lot sizing: results for Trigeiro's random instances


Results obtained using Gurobi for solving the Lot Sizing Problem, using the models described in Mathematical Optimization: Solving Problems using Python and Gurobi. Benchmark instances were generated with Trigeiro's method. CPU time limited to 3600 seconds. (Click on values for selecting data to display.)

Performance dataFactor: lowFactor: medFactor: high
CPU time required [select] [select] [select]
Number of solution failures [select] [select] [select]
Solutions [select] [select] [select]

CPU used

Constraining factor: high (highly constrained instances)

Results obtained using Gurobi for solving the Lot Sizing Problem, using the models described in Mathematical Optimization: Solving Problems using Python and Gurobi. Benchmark instances were generated with Trigeiro's method. CPU time limited to 3600 seconds. (Click on values for selecting data to display.)
CPU used
LabelDescription
std standard model
cut standard model with cutting planes (single item lot sizing cuts; callback on MIPSOL and MIPNODE)
fl facility location formulation

chart
CPU used as a function of instance size, factor=1.1 (high)
InstanceSizePeriodsProductsstdcutfl
lsp_15_6_high_0 90 15 6 0.00 0.00 0.01
lsp_15_6_high_1 90 15 6 9.31 411.15 16.09
lsp_15_6_high_2 90 15 6 21.59 1267.71 36.06
lsp_15_6_high_3 90 15 6 0.00 0.01 0.00
lsp_15_6_high_4 90 15 6 0.11 0.34 0.21
lsp_15_6_high_5 90 15 6 19.09 932.52 16.68
lsp_15_6_high_6 90 15 6 0.00 0.00 0.02
lsp_15_6_high_7 90 15 6 8.21 394.85 12.73
lsp_15_6_high_8 90 15 6 5.88 93.40 3.00
lsp_15_6_high_9 90 15 6 0.01 0.00 0.00
lsp_15_12_high_0 180 15 12 0.00 0.01 0.01
lsp_15_12_high_1 180 15 12 78.29 >3600 48.04
lsp_15_12_high_2 180 15 12 1519.10 >3600 481.23
lsp_15_12_high_3 180 15 12 0.02 0.02 0.00
lsp_15_12_high_4 180 15 12 0.03 0.03 0.02
lsp_15_12_high_5 180 15 12 245.98 >3600 192.02
lsp_15_12_high_6 180 15 12 0.00 0.01 0.00
lsp_15_12_high_7 180 15 12 157.88 >3600 242.55
lsp_15_12_high_8 180 15 12 79.15 >3600 76.15
lsp_15_12_high_9 180 15 12 49.16 3514.88 15.62
lsp_15_24_high_0 360 15 24 0.00 0.02 0.02
lsp_15_24_high_1 360 15 24 >3600 >3600 2713.01
lsp_15_24_high_2 360 15 24 >3600 >3600 >3600
lsp_15_24_high_3 360 15 24 >3600 >3600 759.01
lsp_15_24_high_4 360 15 24 1654.18 >3600 2267.53
lsp_15_24_high_5 360 15 24 3043.21 >3600 169.09
lsp_15_24_high_6 360 15 24 0.02 0.01 0.03
lsp_15_24_high_7 360 15 24 >3600 >3600 >3600
lsp_15_24_high_8 360 15 24 >3600 >3600 1089.67
lsp_15_24_high_9 360 15 24 >3600 >3600 1526.63
lsp_30_6_high_0 180 30 6 0.01 0.00 0.01
lsp_30_6_high_1 180 30 6 821.71 >3600 168.29
lsp_30_6_high_2 180 30 6 >3600 >3600 >3600
lsp_30_6_high_3 180 30 6 0.00 0.01 0.01
lsp_30_6_high_4 180 30 6 0.16 0.34 0.11
lsp_30_6_high_5 180 30 6 >3600 >3600 3199.30
lsp_30_6_high_6 180 30 6 0.01 0.00 0.01
lsp_30_6_high_7 180 30 6 >3600 >3600 2411.71
lsp_30_6_high_8 180 30 6 403.34 >3600 177.47
lsp_30_6_high_9 180 30 6 0.00 0.01 0.02
lsp_30_12_high_0 360 30 12 0.05 0.15 0.11
lsp_30_12_high_1 360 30 12 >3600 >3600 >3600
lsp_30_12_high_2 360 30 12 >3600 >3600 2854.41
lsp_30_12_high_3 360 30 12 0.01 0.02 0.02
lsp_30_12_high_4 360 30 12 >3600 >3600 >3600
lsp_30_12_high_5 360 30 12 >3600 >3600 >3600
lsp_30_12_high_6 360 30 12 0.00 0.02 0.03
lsp_30_12_high_7 360 30 12 >3600 >3600 >3600
lsp_30_12_high_8 360 30 12 >3600 >3600 >3600
lsp_30_12_high_9 360 30 12 >3600 >3600 >3600
lsp_30_24_high_0 720 30 24 0.01 0.01 0.03
lsp_30_24_high_1 720 30 24 >3600 >3600 3091.56
lsp_30_24_high_2 720 30 24 >3600 >3600 >3600
lsp_30_24_high_3 720 30 24 >3600 >3600 >3600
lsp_30_24_high_4 720 30 24 >3600 >3600 >3600
lsp_30_24_high_5 720 30 24 >3600 >3600 >3600
lsp_30_24_high_6 720 30 24 0.01 0.01 0.04
lsp_30_24_high_7 720 30 24 >3600 >3600 1199.79
lsp_30_24_high_8 720 30 24 >3600 >3600 >3600
lsp_30_24_high_9 720 30 24 >3600 >3600 >3600