Speed up gurobi to solve an milp
Answered
I am working with an milp with 58 binary variables, 70 continuous free variables, and 590 nonnegative continuous variables. There are also 1212 constraints. It took Gurobi about 12000 seconds to solve this problem on a work station.
My question is that: what can I do to speed up the solution procedure?
1
-
Can you share a log of the run? (initial portion and final portion)
1 -
Hi,
Gurobi created a mip2_c.tlog folder, and there are 7 files in the folder. I attached 6 jpeg files to this email. The seventh one is called mip2_c.lastbuildstate and I assume that you dont need it.
Thanks in advance.
Ebru0 -
Hi again,
There are
CL.command.1; CL.read.1; CL.write.1; link.read.1; link.write.1; link.command.1
files in mip2_c.tlog. Which one do I have to add as jpeg?
Thanks.
Ebru
0 -
Hi again,
What do you mean by a log of the run? Initial and final portions? It seems that they arent the log files.
Ebru
0 -
Hi Ebru,
I think you posted the log of the build process. Daniel meant the log file from the actual solving process. Something like this:
x7101: 9222 rows, 7101 columns, 54642 nonzeros
Changed value of parameter TimeLimit to 1000.0
Prev: 1e+100 Min: 0.0 Max: 1e+100 Default: 1e+100
Changed value of parameter MIPGap to 0.01
Prev: 0.0001 Min: 0.0 Max: 1e+100 Default: 0.0001
Changed value of parameter Presolve to 2
Prev: -1 Min: -1 Max: 2 Default: -1
Optimize a model with 9222 rows, 7101 columns and 54642 nonzeros
Variable types: 4601 continuous, 2500 integer (2500 binary)
Coefficient statistics:
Matrix range [1e+00, 5e+03]
Objective range [1e+01, 2e+02]
Bounds range [1e+00, 1e+00]
RHS range [1e+00, 1e+06]
Found heuristic solution: objective -0.0000000
Presolve removed 7063 rows and 5102 columns
Presolve time: 0.03s
Presolved: 2159 rows, 1999 columns, 10225 nonzeros
Variable types: 1290 continuous, 709 integer (709 binary)
Presolved: 2159 rows, 1999 columns, 10225 nonzeros
Root relaxation: objective 1.322838e+04, 1310 iterations, 0.05 seconds
Nodes | Current Node | Objective Bounds | Work
Expl Unexpl | Obj Depth IntInf | Incumbent BestBd Gap | It/Node Time
0 0 13228.3750 0 324 -0.00000 13228.3750 - - 0s
H 0 0 4544.0000000 13228.3750 191% - 0s
H 0 0 4710.0000000 13228.3750 181% - 0s
0 0 13224.1250 0 468 4710.00000 13224.1250 181% - 0s
H 0 0 4913.0000000 13224.1250 169% - 0s
0 0 13224.1250 0 475 4913.00000 13224.1250 169% - 0s
0 0 13177.9059 0 503 4913.00000 13177.9059 168% - 0s
H 0 0 5034.0000000 13177.9059 162% - 0s
H 0 0 5076.0000000 13177.9059 160% - 0s
0 0 13175.7566 0 489 5076.00000 13175.7566 160% - 0s
0 0 13175.3460 0 478 5076.00000 13175.3460 160% - 0s
0 0 13175.2162 0 486 5076.00000 13175.2162 160% - 0s
0 0 13175.2037 0 486 5076.00000 13175.2037 160% - 0s
0 0 13132.3616 0 502 5076.00000 13132.3616 159% - 0s
H 0 0 5211.0000000 13132.3616 152% - 0s
0 0 13128.2869 0 509 5211.00000 13128.2869 152% - 0s
0 0 13126.5614 0 502 5211.00000 13126.5614 152% - 0s
0 0 13126.4009 0 498 5211.00000 13126.4009 152% - 0s
0 0 13126.3433 0 496 5211.00000 13126.3433 152% - 0s
0 0 13126.3433 0 497 5211.00000 13126.3433 152% - 0s
0 0 13051.7928 0 501 5211.00000 13051.7928 150% - 0s
0 0 13016.9726 0 503 5211.00000 13016.9726 150% - 0s
0 0 13011.1190 0 488 5211.00000 13011.1190 150% - 0s
0 0 13007.6535 0 494 5211.00000 13007.6535 150% - 0s
0 0 13007.5347 0 500 5211.00000 13007.5347 150% - 1s
0 0 13007.4990 0 493 5211.00000 13007.4990 150% - 1s
0 0 12842.7908 0 452 5211.00000 12842.7908 146% - 1s
0 0 12823.0273 0 450 5211.00000 12823.0273 146% - 1s
0 0 12813.2402 0 472 5211.00000 12813.2402 146% - 1s
0 0 12811.2974 0 463 5211.00000 12811.2974 146% - 1s
0 0 12810.6951 0 470 5211.00000 12810.6951 146% - 1s
0 0 12809.4152 0 468 5211.00000 12809.4152 146% - 1s
0 0 12809.3871 0 459 5211.00000 12809.3871 146% - 1s
0 0 12737.9020 0 478 5211.00000 12737.9020 144% - 1s
0 0 12712.0951 0 456 5211.00000 12712.0951 144% - 1s
0 0 12704.9693 0 462 5211.00000 12704.9693 144% - 1s
0 0 12699.6937 0 454 5211.00000 12699.6937 144% - 1s
0 0 12699.0381 0 465 5211.00000 12699.0381 144% - 1s
0 0 12698.8156 0 481 5211.00000 12698.8156 144% - 1s
0 0 12605.3801 0 454 5211.00000 12605.3801 142% - 1s
H 0 0 5354.0000000 12605.3801 135% - 1s
H 0 0 5639.0000000 12605.3801 124% - 1s
0 0 12585.2066 0 442 5639.00000 12585.2066 123% - 1s
0 0 12574.1142 0 472 5639.00000 12574.1142 123% - 1s
0 0 12567.9716 0 473 5639.00000 12567.9716 123% - 1s
0 0 12567.0267 0 471 5639.00000 12567.0267 123% - 1s
0 0 12566.7444 0 453 5639.00000 12566.7444 123% - 1s
0 0 12508.7174 0 457 5639.00000 12508.7174 122% - 2s
H 0 0 5778.0000000 12508.7174 116% - 2s
0 0 12488.5385 0 466 5778.00000 12488.5385 116% - 2s
0 0 12485.6878 0 489 5778.00000 12485.6878 116% - 2s
0 0 12484.1426 0 437 5778.00000 12484.1426 116% - 2s
0 0 12483.7008 0 464 5778.00000 12483.7008 116% - 2s
0 0 12352.2189 0 450 5778.00000 12352.2189 114% - 2s
0 0 12333.6349 0 447 5778.00000 12333.6349 113% - 2s
0 0 12329.7985 0 441 5778.00000 12329.7985 113% - 2s
0 0 12329.2959 0 449 5778.00000 12329.2959 113% - 2s
0 0 12274.5311 0 444 5778.00000 12274.5311 112% - 2s
H 0 0 5924.0000000 12274.5311 107% - 2s
0 0 12254.4047 0 435 5924.00000 12254.4047 107% - 2s
0 0 12247.5851 0 433 5924.00000 12247.5851 107% - 2s
0 0 12245.8802 0 427 5924.00000 12245.8802 107% - 2s
0 0 12245.1652 0 436 5924.00000 12245.1652 107% - 2s
0 0 12193.2999 0 430 5924.00000 12193.2999 106% - 3s
H 0 0 5995.0000000 12193.2999 103% - 3s
0 0 12156.1850 0 414 5995.00000 12156.1850 103% - 3s
0 0 12146.4421 0 431 5995.00000 12146.4421 103% - 3s
0 0 12142.8597 0 426 5995.00000 12142.8597 103% - 3s
0 0 12141.3942 0 423 5995.00000 12141.3942 103% - 3s
0 0 12141.0968 0 431 5995.00000 12141.0968 103% - 3s
0 0 12062.5994 0 416 5995.00000 12062.5994 101% - 3s
0 0 12042.9788 0 423 5995.00000 12042.9788 101% - 3s
0 0 12027.8896 0 432 5995.00000 12027.8896 101% - 3s
0 0 12025.5845 0 429 5995.00000 12025.5845 101% - 3s
0 0 12025.1990 0 429 5995.00000 12025.1990 101% - 3s
0 0 11969.8560 0 409 5995.00000 11969.8560 100% - 3s
0 0 11950.4257 0 407 5995.00000 11950.4257 99.3% - 3s
0 0 11947.5493 0 407 5995.00000 11947.5493 99.3% - 3s
0 0 11944.6095 0 409 5995.00000 11944.6095 99.2% - 4s
0 0 11944.2350 0 406 5995.00000 11944.2350 99.2% - 4s
0 0 11920.0108 0 410 5995.00000 11920.0108 98.8% - 4s
H 0 0 6104.0000000 11920.0108 95.3% - 4s
0 0 11906.0223 0 391 6104.00000 11906.0223 95.1% - 4s
0 0 11901.2914 0 415 6104.00000 11901.2914 95.0% - 4s
0 0 11900.1720 0 411 6104.00000 11900.1720 95.0% - 4s
0 0 11876.7278 0 401 6104.00000 11876.7278 94.6% - 4s
H 0 0 6397.0000000 11876.7278 85.7% - 4s
0 0 11859.1297 0 412 6397.00000 11859.1297 85.4% - 4s
0 0 11856.2290 0 411 6397.00000 11856.2290 85.3% - 4s
0 0 11854.2437 0 412 6397.00000 11854.2437 85.3% - 4s
0 0 11853.7065 0 409 6397.00000 11853.7065 85.3% - 4s
0 0 11807.2359 0 391 6397.00000 11807.2359 84.6% - 4s
0 0 11800.5755 0 401 6397.00000 11800.5755 84.5% - 4s
0 0 11796.9188 0 404 6397.00000 11796.9188 84.4% - 5s
0 0 11795.6721 0 406 6397.00000 11795.6721 84.4% - 5s
0 0 11780.2100 0 409 6397.00000 11780.2100 84.2% - 5s
H 0 0 6445.0000000 11780.2100 82.8% - 5s
0 0 11772.7237 0 415 6445.00000 11772.7237 82.7% - 5s
0 0 11764.0319 0 414 6445.00000 11764.0319 82.5% - 5s
0 0 11762.5128 0 419 6445.00000 11762.5128 82.5% - 5s
0 0 11762.1102 0 412 6445.00000 11762.1102 82.5% - 5s
0 0 11731.4456 0 418 6445.00000 11731.4456 82.0% - 5s
H 0 0 6506.0000000 11731.4456 80.3% - 5s
0 0 11699.2868 0 411 6506.00000 11699.2868 79.8% - 5s
0 0 11696.7205 0 403 6506.00000 11696.7205 79.8% - 5s
0 0 11695.3694 0 391 6506.00000 11695.3694 79.8% - 5s
0 0 11659.7341 0 385 6506.00000 11659.7341 79.2% - 5s
H 0 0 6585.0000000 11659.7341 77.1% - 6s
0 0 11655.7683 0 406 6585.00000 11655.7683 77.0% - 6s
0 0 11654.8839 0 412 6585.00000 11654.8839 77.0% - 6s
0 0 11645.5597 0 399 6585.00000 11645.5597 76.8% - 6s
0 0 11645.5597 0 321 6585.00000 11645.5597 76.8% - 6s
H 0 0 6648.0000000 11645.5597 75.2% - 7s
0 2 11645.5597 0 321 6648.00000 11645.5597 75.2% - 7s
H 28 28 6738.0000000 11633.9259 72.7% 185 8s
H 59 57 6893.0000000 11633.9259 68.8% 120 8s
H 90 90 6897.0000000 11633.9259 68.7% 100 8s
H 106 105 6944.0000000 11633.9259 67.5% 98.2 9s
H 152 148 7132.0000000 11633.9259 63.1% 94.8 9s
H 182 176 7157.0000000 11633.9259 62.6% 91.1 10s
H 183 178 7207.0000000 11633.9259 61.4% 90.8 10s
H 213 198 7220.0000000 11633.9259 61.1% 90.4 10s
H 274 237 7239.0000000 11633.9259 60.7% 117 11s
H 319 287 7281.0000000 11633.9259 59.8% 109 11s
H 351 313 7298.0000000 11633.9259 59.4% 109 11s
H 381 334 7338.0000000 11633.9259 58.5% 114 12s
H 490 406 7355.0000000 11633.9259 58.2% 113 13s
H 547 449 7377.0000000 11633.8838 57.7% 117 14s
H 574 476 7414.0000000 11633.8838 56.9% 117 14s
617 511 11463.2268 33 330 7414.00000 11633.8838 56.9% 117 15s
H 649 538 7475.0000000 11633.8838 55.6% 116 15s
726 593 11273.0416 47 379 7475.00000 11633.8838 55.6% 118 20s
772 623 10280.8564 8 286 7475.00000 10280.8564 37.5% 111 25s
809 648 10001.5486 19 236 7475.00000 10001.5486 33.8% 106 30s
835 665 9895.23787 46 300 7475.00000 9895.23787 32.4% 103 35s
H 871 652 7517.0000000 9610.13197 27.8% 98.4 40s
H 884 625 7519.0000000 9494.15324 26.3% 96.9 41s
H 903 603 7536.0000000 9391.14066 24.6% 94.9 44s
915 611 9349.55429 22 241 7536.00000 9349.55429 24.1% 93.7 45s
H 915 577 7566.0000000 9327.67002 23.3% 93.7 46s
961 607 9162.35364 13 201 7566.00000 9162.35364 21.1% 89.2 50s
1015 643 8902.13199 22 201 7566.00000 8902.13199 17.7% 84.4 55s
1070 680 8769.14492 100 194 7566.00000 8769.14492 15.9% 80.1 60s
1132 721 8653.90641 5 168 7566.00000 8653.90641 14.4% 75.7 65s
H 1184 711 7574.0000000 8596.14510 13.5% 72.4 70s
H 1224 692 7579.0000000 8559.11574 12.9% 70.0 74s
H 1235 656 7650.0000000 8552.51222 11.8% 69.4 75s
1281 687 8510.87851 48 151 7650.00000 8510.87851 11.3% 66.9 80s
1330 719 8492.13995 24 144 7650.00000 8492.13995 11.0% 64.4 85s
1353 735 8479.31396 16 134 7650.00000 8479.31396 10.8% 63.3 90s
1387 757 8459.20458 24 166 7650.00000 8459.20458 10.6% 61.8 95s
1418 779 8452.24014 6 144 7650.00000 8452.24014 10.5% 305 100s
[...]
94106 66027 8324.70305 65 116 7708.00000 8331.57559 8.09% 117 990s
94983 66799 8288.64108 99 95 7708.00000 8331.54408 8.09% 117 998s
95531 67318 7797.72134 267 45 7708.00000 8331.53962 8.09% 117 1000s
Cutting planes:
Gomory: 175
Cover: 7
MIR: 626
Flow cover: 879
Inf proof: 1
Zero half: 1
Explored 95708 nodes (11238635 simplex iterations) in 1000.03 seconds
Thread count was 4 (of 4 available processors)
Solution count 10: 7708 7658 7654 ... 7517
Time limit reached
Best objective 7.708000000000e+03, best bound 8.331000000000e+03, gap 8.0825%0 -
Hi,
I have a similar problem:
I am using Gurobi to solve a power plant dispatch problem (continuous vars.) including an investment problem (binary vars.) -> MIP. It seems that the root relaxation is using just one thread, although my PC has 12 threads (which I also included in the threads parameter).
Is there a possibility to speed up the root relaxation? In this form, the solving process is very unsatisfactory. Thank you for any advice!
Best,
AndreasLogfile (including the root simplex, only)
Gurobi 8.1.1 (win64, Python) logging started 04/17/19 11:28:20
Academic license - for non-commercial use only
Read LP format model from file C:\Users\simulant\AppData\Local\Temp\tmpwf_ohr5l.pyomo.lp
Reading time = 19.02 seconds
x2698135: 3539080 rows, 2452855 columns, 14651505 nonzeros
Changed value of parameter MipGap to 0.01
Prev: 0.0001 Min: 0.0 Max: 1e+100 Default: 0.0001
Parameter Method unchanged
Value: -1 Min: -1 Max: 5 Default: -1
Parameter OutputFlag unchanged
Value: 1 Min: 0 Max: 1 Default: 1
Changed value of parameter DisplayInterval to 30
Prev: 5 Min: 1 Max: 2000000000 Default: 5
Parameter LogToConsole unchanged
Value: 1 Min: 0 Max: 1 Default: 1
Optimize a model with 3539080 rows, 2452855 columns and 14651505 nonzeros
Variable types: 2452834 continuous, 21 integer (21 binary)
Coefficient statistics:
Matrix range [1e-06, 1e+05]
Objective range [1e+00, 1e+00]
Bounds range [1e+00, 1e+00]
RHS range [8e-03, 6e+02]
Presolve removed 1957549 rows and 1116576 columns
Presolve time: 16.71s
Presolved: 1581531 rows, 1336279 columns, 7197309 nonzeros
Variable types: 1336265 continuous, 14 integer (14 binary)
Root simplex log...
Iteration Objective Primal Inf. Dual Inf. Time
0 -2.1234281e+08 5.820970e+09 0.000000e+00 215s
Gurobi 8.1.1 (win64, Python) logging started 04/17/19 11:32:19
Academic license - for non-commercial use only
20440 -2.0821339e+08 1.332699e+10 0.000000e+00 240s
82317 -1.9040451e+08 7.055455e+09 0.000000e+00 271s
97742 -1.8206249e+08 8.798116e+09 0.000000e+00 301s
110996 -1.7502490e+08 6.930994e+09 0.000000e+00 331s
122719 -1.6994886e+08 1.090976e+10 0.000000e+00 361s
132591 -1.6635742e+08 1.280828e+10 0.000000e+00 391s
141229 -1.6378041e+08 9.291548e+09 0.000000e+00 421s
149250 -1.6205796e+08 9.081888e+09 0.000000e+00 453s
156654 -1.6081303e+08 8.232228e+09 0.000000e+00 481s
165292 -1.5959797e+08 7.957718e+09 0.000000e+00 513s
171462 -1.5885527e+08 6.724940e+09 0.000000e+00 542s
178249 -1.5786185e+08 1.153445e+10 0.000000e+00 571s
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1888447 -6.2136634e+07 2.006242e+12 0.000000e+00 11018s
1889681 -6.2102376e+07 6.616256e+09 0.000000e+00 11041s
1891532 -6.2078574e+07 4.547093e+09 0.000000e+00 11072s
1893383 -6.2061936e+07 2.364677e+09 0.000000e+00 11104s
1894550 -6.2038881e+07 2.204035e+10 0.000000e+00 11136s
1896401 -6.2023328e+07 3.857498e+10 0.000000e+00 11170s
1897635 -6.2000106e+07 6.530826e+10 0.000000e+00 11195s
1898842 -6.1935712e+07 3.390945e+09 0.000000e+00 11221s
1900576 -6.1891594e+07 7.026196e+10 0.000000e+00 11262s
1901810 -6.1870146e+07 3.953342e+10 0.000000e+00 11287s
1903044 -6.1859701e+07 1.414957e+10 0.000000e+00 11311s
1904858 -6.1770673e+07 1.065681e+10 0.000000e+00 11349s
1906055 -6.1759768e+07 4.490701e+09 0.000000e+00 11378s
1907289 -6.1739108e+07 2.163624e+09 0.000000e+00 11401s
1909036 -6.1719381e+07 2.059438e+09 0.000000e+00 11444s
1910270 -6.1695039e+07 4.052858e+09 0.000000e+00 11464s
1911467 -6.1684497e+07 5.728554e+09 0.000000e+00 11491s
1913318 -6.1613160e+07 2.409750e+09 0.000000e+00 11525s
1914552 -6.1601361e+07 9.433447e+09 0.000000e+00 11551s
1916403 -6.1584779e+07 2.110972e+10 0.000000e+00 11581s
1918254 -6.1543022e+07 4.041024e+09 0.000000e+00 11620s
1919488 -6.1529901e+07 3.207612e+10 0.000000e+00 11644s
1920615 -6.1500072e+07 4.669846e+09 0.000000e+00 11670s
1923083 -6.1403252e+07 1.629685e+11 0.000000e+00 11711s
1924210 -6.1386935e+07 3.423996e+09 0.000000e+00 11740s
1926061 -6.1376841e+07 1.034225e+09 0.000000e+00 11763s
1927912 -6.1357273e+07 3.304640e+10 0.000000e+00 11796s
1929146 -6.1336041e+07 3.640616e+09 0.000000e+00 11821s
1930970 -6.1302516e+07 1.947413e+09 0.000000e+00 11856s
1932821 -6.1230062e+07 2.047166e+09 0.000000e+00 11890s
1934672 -6.0956274e+07 5.863401e+09 0.000000e+00 11916s
1936523 -6.0939243e+07 4.398579e+09 0.000000e+00 11948s
1937757 -6.0885391e+07 5.542641e+09 0.000000e+00 11975s
1938914 -6.0752240e+07 3.695716e+10 0.000000e+00 12006s
1940101 -6.0735526e+07 1.574090e+10 0.000000e+00 12034s
1941952 -6.0718231e+07 4.571068e+09 0.000000e+00 12067s
1943059 -6.0695540e+07 1.318744e+10 0.000000e+00 12097s
1944266 -6.0678435e+07 6.527405e+09 0.000000e+00 12126s
1945500 -6.0544707e+07 3.174918e+09 0.000000e+00 12151s
1947304 -6.0524137e+07 1.630815e+10 0.000000e+00 12190s
1948538 -6.0516332e+07 1.431418e+10 0.000000e+00 12212s
1949645 -6.0457016e+07 1.260950e+09 0.000000e+00 12241s
1951469 -6.0394796e+07 2.623129e+11 0.000000e+00 12279s
1952703 -6.0373341e+07 1.466611e+10 0.000000e+00 12302s
1954554 -6.0320250e+07 2.156706e+09 0.000000e+00 12343s
1955681 -6.0264108e+07 1.002586e+10 0.000000e+00 12370s
1956828 -6.0214858e+07 2.145915e+09 0.000000e+00 12397s
1958642 -6.0186060e+07 1.655322e+10 0.000000e+00 12434s
1959876 -6.0172483e+07 5.254195e+10 0.000000e+00 12459s
1961110 -6.0155330e+07 9.685635e+08 0.000000e+00 12481s
1962961 -6.0113740e+07 2.765124e+10 0.000000e+00 12514s
1964812 -5.9900976e+07 4.970726e+10 0.000000e+00 12547s
1965919 -5.9875530e+07 2.965126e+09 0.000000e+00 12579s
1967770 -5.9850323e+07 5.796683e+09 0.000000e+00 12611s
1969004 -5.9838823e+07 5.178987e+09 0.000000e+00 12631s
1970855 -5.9741004e+07 6.752038e+09 0.000000e+00 12667s
1972042 -5.9701546e+07 1.508709e+11 0.000000e+00 12696s
1973276 -5.9686405e+07 2.236884e+09 0.000000e+00 12723s
1975000 -5.9610892e+07 5.456838e+09 0.000000e+00 12765s
1976234 -5.9594899e+07 8.394159e+09 0.000000e+00 12793s
1977468 -5.9573413e+07 2.739889e+09 0.000000e+00 12816s
1978645 -5.9532327e+07 6.016073e+09 0.000000e+00 12844s
1980459 -5.9416311e+07 1.067619e+11 0.000000e+00 12885s
1981486 -5.9391758e+07 1.074870e+11 0.000000e+00 12911s
1982663 -5.9374864e+07 1.048239e+10 0.000000e+00 12942s
1983880 -5.9341915e+07 3.010757e+09 0.000000e+00 12972s
1984820 -5.9280995e+07 5.666579e+09 0.000000e+00 13004s
1985900 -5.9258035e+07 5.613022e+10 0.000000e+00 13034s
1987134 -5.9243327e+07 4.977646e+09 0.000000e+00 13061s0 -
Hi Andreas,
some things caught my eye:
- your model is, I would say, a rather big one. 2.5m variables, 3.5m constraints and 14m non-zeros is something. However the numbers are halved after presolving. You could try to enable a more aggressive presolving. See http://www.gurobi.com/documentation/8.1/refman/presolve.html#parameter:Presolve
- The entries in your matrix span 10 orders of magnitude (10^-6 - 10^5). This will most likely lead to some numerical difficulties. You could try to activate some parameters to help with numerically challenging problems. See the manual for more details: http://www.gurobi.com/documentation/8.1/refman/numerics_gurobi_guidelines.html#sec:Numerics
- You could also try some other parameters:
- Use barrier for solving nodes in the branch-and-bound tree via http://www.gurobi.com/documentation/8.1/refman/nodemethod.html#parameter:NodeMethod
- Use concurrent (or barrier) method explicitly for solving the root relaxation: http://www.gurobi.com/documentation/8.1/refman/method.html#parameter:Method
- Play around with http://www.gurobi.com/documentation/8.1/refman/quad.html#parameter:Quad
Maybe you could also try to adjust the scales in your model before you plug it into gurobi. It will definitely improve solving time.
0 -
Dear Jakob,
thanks a lot for your answer. As you mentioned the model is on the rather big side. I managed to decrease the computation time by reducing the binary variables (investment decision for energy storages). As you mentioned I also managed it to reduce the span of the matrix, mostly by reducing the scale of the objective.
Thanks also a lot for suggesting to play around with the parameters. As the computation time is still challenging, I am still playing around with the parameters.
0 -
Hi,
Thanks a lot for the helpful comments GUROBI provided above,I have a similar problem for speeding up the solving process in GUROBI. The model established is based on Yalmip toolbox in MATLAB environment.
My log file is below, is there any acceleration strategy on the premise of not changing my model?(I find the MIP gap decreases very slow over a period of time)Gurobi Optimizer version 9.1.0 build v9.1.0rc0 (win64)
Thread count: 4 physical cores, 8 logical processors, using up to 8 threads
Optimize a model with 27000 rows, 8679 columns and 72771 nonzeros
Model fingerprint: 0x526bd688
Variable types: 6540 continuous, 2139 integer (2139 binary)
Coefficient statistics:
Matrix range [7e-03, 2e+03]
Objective range [8e-01, 2e+02]
Bounds range [1e+00, 1e+00]
RHS range [9e-01, 6e+03]
Presolve removed 17072 rows and 5328 columns
Presolve time: 0.59s
Presolved: 9928 rows, 3351 columns, 39753 nonzeros
Variable types: 2280 continuous, 1071 integer (1043 binary)
Root relaxation: objective 7.638142e+04, 6272 iterations, 0.48 seconds
Nodes | Current Node | Objective Bounds | Work
Expl Unexpl | Obj Depth IntInf | Incumbent BestBd Gap | It/Node Time
0 0 76466.8969 0 292 - 76466.8969 - - 2s
0 0 79356.6460 0 602 - 79356.6460 - - 7s
0 0 79591.8973 0 623 - 79591.8973 - - 9s
0 0 79621.2829 0 628 - 79621.2829 - - 10s
0 0 79634.1057 0 623 - 79634.1057 - - 10s
0 0 79645.3705 0 624 - 79645.3705 - - 11s
0 0 79646.7726 0 616 - 79646.7726 - - 11s
0 0 79647.8003 0 619 - 79647.8003 - - 11s
0 0 79647.9715 0 614 - 79647.9715 - - 11s
0 0 80643.6560 0 641 - 80643.6560 - - 14s
0 0 80783.9762 0 674 - 80783.9762 - - 15s
0 0 80809.9920 0 662 - 80809.9920 - - 15s
0 0 80816.1363 0 667 - 80816.1363 - - 15s
0 0 80819.1530 0 504 - 80819.1530 - - 16s
0 0 80819.8971 0 502 - 80819.8971 - - 16s
0 0 80946.4074 0 537 - 80946.4074 - - 17s
0 0 80973.8514 0 554 - 80973.8514 - - 17s
0 0 80980.6396 0 646 - 80980.6396 - - 17s
0 0 80983.2064 0 540 - 80983.2064 - - 17s
0 0 80983.2714 0 540 - 80983.2714 - - 17s
0 0 81011.9612 0 553 - 81011.9612 - - 18s
0 0 81012.5504 0 472 - 81012.5504 - - 18s
0 0 81033.1143 0 573 - 81033.1143 - - 19s
0 0 81033.9388 0 495 - 81033.9388 - - 19s
0 0 81040.4133 0 519 - 81040.4133 - - 19s
0 0 81041.9851 0 575 - 81041.9851 - - 20s
0 0 81042.9181 0 547 - 81042.9181 - - 20s
0 0 81045.0135 0 481 - 81045.0135 - - 20s
0 0 81045.3299 0 499 - 81045.3299 - - 20s
0 0 81056.2358 0 528 - 81056.2358 - - 21s
0 0 81056.2358 0 454 - 81056.2358 - - 23s
0 2 81056.2358 0 454 - 81056.2358 - - 25s
19 24 81616.8086 6 498 - 81393.9652 - 2831 30s
68 67 82186.7333 13 401 - 81393.9652 - 2168 35s
147 123 82636.0132 5 468 - 81546.3439 - 1751 40s
204 154 86282.1246 8 429 - 81546.3439 - 1732 45s
340 274 83015.8887 11 480 - 81546.3439 - 1414 50s
H 449 344 88608.494118 81546.3439 7.97% 1262 53s
482 392 85532.5753 18 366 88608.4941 81546.3439 7.97% 1239 55s
H 587 433 88210.812234 81546.3439 7.56% 1097 56s
H 632 431 87945.317075 81546.3439 7.28% 1048 57s
* 635 425 110 87642.695712 81546.3439 6.96% 1043 57s
667 424 85081.4704 18 379 87642.6957 81546.3439 6.96% 1034 60s
H 673 421 87586.603438 81546.3439 6.90% 1038 60s
718 440 82294.3619 10 312 87586.6034 81680.6793 6.74% 1062 65s
810 471 83035.1976 14 345 87586.6034 81739.7942 6.68% 1080 71s
H 842 473 87571.064736 81792.0185 6.60% 1077 72s
860 477 82239.7374 11 290 87571.0647 81792.0185 6.60% 1079 75s
H 883 475 87510.612088 81792.0185 6.53% 1087 77s
H 925 478 87386.178543 81792.0185 6.40% 1084 79s
940 485 86665.8794 39 100 87386.1785 81881.7641 6.30% 1093 81s
H 1005 497 87356.902165 81934.7548 6.21% 1103 84s
1023 506 84141.8441 16 250 87356.9022 81989.6485 6.14% 1100 86s
H 1065 494 87328.450555 81989.6485 6.11% 1094 89s
1087 494 cutoff 16 87328.4506 82022.8563 6.08% 1110 91s
1147 494 82299.7362 12 378 87328.4506 82043.1693 6.05% 1130 96s
H 1183 501 87322.456165 82069.9668 6.02% 1128 98s
H 1189 492 87265.052207 82069.9668 5.95% 1132 98s
1214 497 82812.5101 12 405 87265.0522 82069.9668 5.95% 1138 100s
H 1255 492 87142.498154 82069.9668 5.82% 1134 103s
1283 506 cutoff 10 87142.4982 82139.3713 5.74% 1135 106s
1315 499 85260.0183 14 410 87142.4982 82177.2791 5.70% 1148 110s
H 1387 458 86848.877964 82182.2090 5.37% 1145 116s
1484 495 84001.2286 19 269 86848.8780 82295.9650 5.24% 1146 122s
1548 500 infeasible 5 86848.8780 82306.8980 5.23% 1134 126s
1638 513 cutoff 13 86848.8780 82414.5498 5.11% 1148 133s
H 1660 496 86754.278083 82447.4243 4.96% 1152 133s
H 1662 494 86745.704184 82447.4243 4.96% 1153 133s
1666 497 cutoff 14 86745.7042 82447.8054 4.95% 1155 136s
H 1712 490 86694.662205 82447.8054 4.90% 1159 142s
H 1721 492 86672.162356 82447.8054 4.87% 1162 146s
1778 500 83752.5579 14 278 86672.1624 82519.7457 4.79% 1162 150s
1917 521 cutoff 19 86672.1624 82600.3795 4.70% 1173 159s
H 1922 517 86637.661497 82600.3795 4.66% 1179 159s
1956 549 84078.1795 16 446 86637.6615 82637.9547 4.62% 1191 164s
2053 559 83113.2176 15 286 86637.6615 82660.8332 4.59% 1178 168s
2126 557 infeasible 16 86637.6615 82688.2163 4.56% 1177 173s
2199 566 84579.1692 19 228 86637.6615 82691.0433 4.56% 1176 177s
2262 560 cutoff 14 86637.6615 82789.1371 4.44% 1173 185s
2341 584 84210.5180 11 470 86637.6615 82853.7885 4.37% 1179 192s
2395 584 infeasible 28 86637.6615 82855.4339 4.37% 1180 197s
2483 588 cutoff 17 86637.6615 82922.1737 4.29% 1178 203s
2593 604 83419.7455 12 404 86637.6615 82970.6813 4.23% 1172 208s
2703 601 86023.3241 31 224 86637.6615 83003.7530 4.19% 1162 214s
2819 614 84144.1139 13 446 86637.6615 83053.3745 4.14% 1152 220s
2925 617 84504.6191 16 271 86637.6615 83148.0567 4.03% 1145 227s
H 2995 616 86623.862569 83178.5320 3.98% 1145 227s
3016 629 83697.7668 19 295 86623.8626 83200.0999 3.95% 1145 233s
3143 645 84359.3108 18 404 86623.8626 83266.6456 3.88% 1139 243s
3255 670 84873.4138 17 294 86623.8626 83319.1918 3.81% 1136 249s
3407 667 84913.6733 18 366 86623.8626 83363.6513 3.76% 1126 258s
3500 660 84985.0231 20 320 86623.8626 83368.8960 3.76% 1125 266s
3647 669 cutoff 20 86623.8626 83399.3357 3.72% 1120 274s
3800 651 84753.3432 21 289 86623.8626 83474.8551 3.64% 1116 282s
3952 649 infeasible 20 86623.8626 83517.0218 3.59% 1114 290s
4099 643 cutoff 17 86623.8626 83589.6165 3.50% 1114 302s
4261 650 cutoff 19 86623.8626 83636.0055 3.45% 1110 311s
4376 683 84828.1447 19 263 86623.8626 83711.9023 3.36% 1110 321s
4552 699 86033.8525 14 356 86623.8626 83771.0526 3.29% 1108 334s
4757 717 85767.7188 13 253 86623.8626 83866.9452 3.18% 1101 346s
4959 759 85774.1751 7 453 86623.8626 83969.6766 3.06% 1098 358s
5206 760 85948.6354 20 454 86623.8626 84020.7452 3.01% 1090 376s
5209 762 84772.1541 26 463 86623.8626 84020.7452 3.01% 1090 383s
5210 763 85501.9545 15 654 86623.8626 84020.7452 3.01% 1089 385s
5216 767 84097.0976 12 531 86623.8626 84020.7452 3.01% 1088 390s
5218 768 84953.3610 17 587 86623.8626 84020.7452 3.01% 1088 398s
5221 773 84020.7452 11 562 86623.8626 84020.7452 3.01% 1098 423s
5223 776 84020.7452 12 360 86623.8626 84020.7452 3.01% 1099 448s
5227 779 84020.7452 13 364 86623.8626 84020.7452 3.01% 1101 466s
5231 782 84020.7452 13 560 86623.8626 84020.7452 3.01% 1103 482s
5235 784 84020.7452 14 422 86623.8626 84020.7452 3.01% 1106 486s
5243 792 84020.7452 15 372 86623.8626 84020.7452 3.01% 1111 493s
5250 797 84020.7452 16 335 86623.8626 84020.7452 3.01% 1111 495s
5277 815 84020.7452 19 437 86623.8626 84020.7452 3.01% 1110 501s
5294 821 84020.7452 22 357 86623.8626 84020.7452 3.01% 1113 505s
5325 831 cutoff 26 86623.8626 84020.7452 3.01% 1118 511s
5352 833 84312.2899 29 335 86623.8626 84020.7452 3.01% 1120 516s
5392 842 84020.7452 21 486 86623.8626 84020.7452 3.01% 1121 521s
5425 860 84020.7452 31 257 86623.8626 84020.7452 3.01% 1122 525s
5476 862 84020.7452 19 369 86623.8626 84020.7452 3.01% 1120 531s
5513 860 84311.2909 29 326 86623.8626 84020.7452 3.01% 1126 537s
5536 859 infeasible 30 86623.8626 84020.7452 3.01% 1129 540s
5562 872 84020.7452 21 466 86623.8626 84020.7452 3.01% 1137 545s
5618 873 cutoff 32 86623.8626 84020.7452 3.01% 1140 552s
5641 864 84020.7452 22 410 86623.8626 84020.7452 3.01% 1143 555s
5688 864 cutoff 26 86623.8626 84020.7452 3.01% 1150 561s
5718 869 84020.7452 19 388 86623.8626 84020.7452 3.01% 1152 566s
5797 854 86164.0258 23 381 86623.8626 84020.7452 3.01% 1154 572s
5814 855 85214.7477 24 445 86623.8626 84020.7452 3.01% 1155 576s
5854 847 85453.6712 22 304 86623.8626 84020.7452 3.01% 1157 580s
5945 846 84020.7452 22 426 86623.8626 84020.7452 3.01% 1158 589s
5985 837 84033.6536 19 569 86623.8626 84020.7452 3.01% 1158 594s
6036 833 84020.7452 18 343 86623.8626 84020.7452 3.01% 1160 599s
6081 827 cutoff 25 86623.8626 84020.7452 3.01% 1161 606s
6116 842 84020.7452 20 530 86623.8626 84020.7452 3.01% 1164 612s
6156 829 84020.7452 22 540 86623.8626 84020.7452 3.01% 1167 618s
6199 826 84840.1733 25 448 86623.8626 84020.7452 3.01% 1172 624s
6246 830 84521.6059 28 397 86623.8626 84020.7452 3.01% 1176 630s
6298 823 85485.2662 32 330 86623.8626 84020.7452 3.01% 1174 643s
6370 801 85050.8526 24 387 86623.8626 84020.7452 3.01% 1172 649s
6417 787 84020.7452 23 371 86623.8626 84020.7452 3.01% 1173 656s
6476 779 84762.6991 20 370 86623.8626 84020.7452 3.01% 1177 662s
6505 790 84058.5426 20 445 86623.8626 84020.7452 3.01% 1179 669s
H 6560 733 86623.862547 84020.7452 3.01% 1175 669s
6614 724 84164.2068 22 281 86623.8625 84020.7452 3.01% 1176 675s
6678 702 84126.3139 22 361 86623.8625 84020.7452 3.01% 1182 683s
6745 680 84020.7452 22 376 86623.8625 84020.7452 3.01% 1188 694s
6778 687 84382.7037 21 459 86623.8625 84020.7452 3.01% 1191 703s
6853 662 85516.8037 23 351 86623.8625 84020.7452 3.01% 1195 715s
6885 660 84020.7452 25 213 86623.8625 84020.7452 3.01% 1195 726s
6964 631 84020.7452 19 384 86623.8625 84020.7452 3.01% 1196 734s
7044 618 84801.3289 21 431 86623.8625 84020.7452 3.01% 1202 743s
7124 621 84257.6066 25 336 86623.8625 84020.7452 3.01% 1205 754s
7207 613 85246.7243 21 453 86623.8625 84020.7452 3.01% 1209 764s
7285 610 86086.8883 25 370 86623.8625 84020.7452 3.01% 1218 775s
7422 571 85492.1246 26 387 86623.8625 84020.7452 3.01% 1218 785s
7530 580 infeasible 20 86623.8625 84020.7452 3.01% 1223 795s
7640 585 84031.6597 20 548 86623.8625 84020.7452 3.01% 1227 806s
7773 588 cutoff 25 86623.8625 84020.7452 3.01% 1230 819s
7804 620 84365.0393 29 326 86623.8625 84020.7452 3.01% 1231 832s
7955 650 infeasible 25 86623.8625 84020.7452 3.01% 1228 846s
8112 672 infeasible 25 86623.8625 84020.7452 3.01% 1227 858s
8273 688 cutoff 30 86623.8625 84020.7452 3.01% 1228 870s
8426 706 84113.0189 18 357 86623.8625 84020.7452 3.01% 1228 886s
8553 729 84341.0794 24 496 86623.8625 84020.7452 3.01% 1235 900s
8630 744 84371.2880 24 286 86623.8625 84020.7452 3.01% 1236 918s
8787 766 infeasible 22 86623.8625 84020.7452 3.01% 1238 933s
8927 775 84805.4718 27 459 86623.8625 84020.7452 3.01% 1246 952s
9140 799 cutoff 25 86623.8625 84020.7452 3.01% 1247 970s
9261 800 84020.7452 20 571 86623.8625 84020.7452 3.01% 1255 989s
9333 810 cutoff 22 86623.8625 84020.7452 3.01% 1261 1007s
9513 844 86209.8795 20 384 86623.8625 84020.7452 3.01% 1260 1029s
9730 854 84020.7452 22 483 86623.8625 84020.7452 3.01% 1262 1050s
9854 852 cutoff 27 86623.8625 84020.7452 3.01% 1273 1071s
10037 872 84037.9645 21 555 86623.8625 84020.7452 3.01% 1277 1094s
10211 882 cutoff 25 86623.8625 84020.7452 3.01% 1286 1116s
10445 916 86016.5175 25 233 86623.8625 84020.7452 3.01% 1291 1142s
10752 928 85781.6888 24 223 86623.8625 84020.7452 3.01% 1290 1161s
10932 932 85518.5818 28 479 86623.8625 84020.7452 3.01% 1296 1183s
11063 937 86048.8654 26 354 86623.8625 84020.7452 3.01% 1303 1212s
11330 938 cutoff 24 86623.8625 84020.7452 3.01% 1309 1235s
11597 964 infeasible 22 86623.8625 84020.7452 3.01% 1313 1263s
11888 992 85534.5598 26 311 86623.8625 84020.7452 3.01% 1315 1289s
12228 1014 cutoff 24 86623.8625 84038.2264 2.98% 1314 1318s
12503 1021 cutoff 28 86623.8625 84126.3697 2.88% 1316 1349s
12841 1041 86227.2189 25 182 86623.8625 84206.9957 2.79% 1316 1378s
13260 1049 86383.9373 35 132 86623.8625 84313.8616 2.67% 1308 1416s
13638 1028 85683.7918 23 487 86623.8625 84391.0694 2.58% 1305 1452s
13944 1028 86565.2278 23 330 86623.8625 84493.0948 2.46% 1311 1487s
14342 980 cutoff 25 86623.8625 84604.4291 2.33% 1308 1521s
14831 964 cutoff 27 86623.8625 84772.4154 2.14% 1300 1553s
15011 884 cutoff 28 86623.8625 84829.8526 2.07% 1298 1603s
15466 827 86026.3791 27 225 86623.8625 84905.5078 1.98% 1293 1635s
16020 811 85754.5108 24 422 86623.8625 85140.8808 1.71% 1283 1672s
16642 717 cutoff 30 86623.8625 85283.5126 1.55% 1267 1716s
17402 568 cutoff 27 86623.8625 85460.8009 1.34% 1242 1750s
18178 523 86091.9724 41 174 86623.8625 85679.5881 1.09% 1217 1779s
19106 439 86385.0540 42 171 86623.8625 85913.0164 0.82% 1181 1804s
20387 440 cutoff 37 86623.8625 86147.6750 0.55% 1123 1828s
20446 549 cutoff 45 86623.8625 86152.2201 0.54% 1120 1852s
22449 319 cutoff 24 86623.8625 86323.9710 0.35% 1034 1875s
25186 225 86615.1596 50 92 86623.8625 86492.4935 0.15% 931 1883s
25698 124 cutoff 54 86623.8625 86536.6697 0.10% 914 1887s
H26205 124 86623.535168 86575.6933 0.06% 898 1887s
Cutting planes:
Learned: 70
Gomory: 12
Cover: 146
Implied bound: 890
Projected implied bound: 218
Clique: 112
MIR: 860
StrongCG: 5
Flow cover: 1124
GUB cover: 18
Inf proof: 1
Zero half: 34
RLT: 117
Relax-and-lift: 299
Explored 26547 nodes (23617740 simplex iterations) in 1889.42 seconds
Thread count was 8 (of 8 available processors)
Solution count 10: 86623.5 86623.9 86623.9 ... 87142.5
Optimal solution found (tolerance 1.00e-04)
Best objective 8.662353516758e+04, best bound 8.662353516758e+04, gap 0.0000%0 -
Hi Yansong,
You should have a look at the documentation of Gurobi's most important parameters.
In particular, testing MIPFocus = 1, 2, or 3 should be a good start. Other than that, you could use Gurobi's tuning tool.
Best regards,
Jaromił0 -
Dear Jaromił,
Thank you for your valuable reply. I have tried to change the parameters,like MIPFocus, ImproveStartGap, etc.However, I find the solving time has little change. I tried to change the objective function of my model,I find the relative gap appears after a few seconds,which seems to be longer than the log file I provided above. The new log file is below, I wonder if there are some methods to accelerate the time when the relative gap appears.
Gurobi Optimizer version 9.1.0 build v9.1.0rc0 (win64)
Thread count: 4 physical cores, 8 logical processors, using up to 8 threads
Optimize a model with 27000 rows, 8679 columns and 72771 nonzeros
Model fingerprint: 0xca3429af
Variable types: 6540 continuous, 2139 integer (2139 binary)
Coefficient statistics:
Matrix range [7e-03, 2e+03]
Objective range [8e-01, 1e+00]
Bounds range [1e+00, 1e+00]
RHS range [9e-01, 6e+03]
Presolve removed 17072 rows and 5328 columns
Presolve time: 0.45s
Presolved: 9928 rows, 3351 columns, 39753 nonzeros
Variable types: 2280 continuous, 1071 integer (1043 binary)
Root relaxation: objective 1.102392e+05, 10222 iterations, 1.17 seconds
Nodes | Current Node | Objective Bounds | Work
Expl Unexpl | Obj Depth IntInf | Incumbent BestBd Gap | It/Node Time
0 0 110239.236 0 303 - 110239.236 - - 2s
0 0 110998.395 0 707 - 110998.395 - - 8s
0 0 111235.863 0 725 - 111235.863 - - 10s
0 0 111284.969 0 700 - 111284.969 - - 12s
0 0 111297.461 0 691 - 111297.461 - - 13s
0 0 111298.125 0 710 - 111298.125 - - 13s
0 0 111298.484 0 707 - 111298.484 - - 13s
0 0 111298.535 0 705 - 111298.535 - - 13s
0 0 111497.441 0 736 - 111497.441 - - 17s
0 0 111555.351 0 740 - 111555.351 - - 19s
0 0 111574.607 0 702 - 111574.607 - - 20s
0 0 111574.607 0 738 - 111574.607 - - 21s
0 0 111574.607 0 754 - 111574.607 - - 22s
0 0 111574.607 0 758 - 111574.607 - - 23s
0 0 111662.407 0 722 - 111662.407 - - 25s
0 0 111668.410 0 730 - 111668.410 - - 27s
0 0 111673.241 0 721 - 111673.241 - - 28s
0 0 111673.455 0 730 - 111673.455 - - 29s
0 0 111714.004 0 696 - 111714.004 - - 31s
0 0 111716.127 0 648 - 111716.127 - - 33s
0 0 111716.896 0 700 - 111716.896 - - 34s
0 0 111716.936 0 692 - 111716.936 - - 34s
0 0 111732.645 0 750 - 111732.645 - - 36s
0 0 111733.946 0 726 - 111733.946 - - 38s
0 0 111734.918 0 666 - 111734.918 - - 38s
0 0 111735.003 0 726 - 111735.003 - - 40s
0 0 111735.814 0 719 - 111735.814 - - 41s
0 0 111736.091 0 731 - 111736.091 - - 43s
0 0 111736.268 0 752 - 111736.268 - - 45s
[...]
H12841 533 113192.69092 113156.814 0.03% 1526 1610s
13226 530 113159.613 49 148 113192.691 113159.613 0.03% 1498 1623s
H13339 511 113192.61319 113159.613 0.03% 1492 1623s
13582 351 113190.255 44 140 113192.613 113159.613 0.03% 1474 1637s
14502 126 113174.977 53 65 113192.613 113170.963 0.02% 1396 1646s
Cutting planes:
Learned: 54
Gomory: 1
Cover: 191
Implied bound: 338
Projected implied bound: 147
Clique: 76
MIR: 364
StrongCG: 2
Flow cover: 959
GUB cover: 11
Inf proof: 2
Zero half: 17
RLT: 49
Relax-and-lift: 105
Explored 15247 nodes (23648618 simplex iterations) in 1647.00 seconds
Thread count was 8 (of 8 available processors)
Solution count 10: 113193 113193 113200 ... 113348
Optimal solution found (tolerance 1.00e-04)
Best objective 1.131926131931e+05, best bound 1.131857704849e+05, gap 0.0060%0 -
It seems like you did not change any parameter. When you change the parameter, you should see a line similar to
Changed value of parameter MIPFocus to 3
Prev: 0 Min: 0.0 Max: 3 Default: 00 -
Dear Jaromił,
Thank you for your reply, I didn't express it clear just now. At first,I tried to select the proper parameters(for example,if the MIPFocus is set to 3), the log file is something like(I didn't see a line prompt like the prompt above,but I think the MIPFocus has been changed,maybe it is relative to the display mode of the Yalmip toolbox),
Gurobi Optimizer version 9.1.0 build v9.1.0rc0 (win64)
Thread count: 4 physical cores, 8 logical processors, using up to 8 threads
Optimize a model with 27000 rows, 8679 columns and 72771 nonzeros
Model fingerprint: 0x526bd688
Variable types: 6540 continuous, 2139 integer (2139 binary)
Coefficient statistics:
Matrix range [7e-03, 2e+03]
Objective range [8e-01, 2e+02]
Bounds range [1e+00, 1e+00]
RHS range [9e-01, 6e+03]
Presolve removed 17090 rows and 5332 columns
Presolve time: 0.66s
Presolved: 9910 rows, 3347 columns, 39803 nonzeros
Variable types: 2279 continuous, 1068 integer (1040 binary)
Presolve removed 482 rows and 25 columns
Presolved: 9428 rows, 3763 columns, 39061 nonzeros
Root relaxation: objective 7.647595e+04, 7143 iterations, 0.78 seconds
Nodes | Current Node | Objective Bounds | Work
Expl Unexpl | Obj Depth IntInf | Incumbent BestBd Gap | It/Node Time
0 0 76475.9469 0 192 - 76475.9469 - - 2s
0 0 79416.8948 0 448 - 79416.8948 - - 6s
0 0 79594.1643 0 580 - 79594.1643 - - 9s
[...]
28123 1066 86609.2590 60 41 86623.5352 86609.2524 0.02% 808 2578s
28523 935 cutoff 54 86623.5352 86612.1262 0.01% 797 2581s
Cutting planes:
Learned: 49
Gomory: 8
Cover: 199
Implied bound: 539
Projected implied bound: 206
Clique: 129
MIR: 1812
StrongCG: 13
Flow cover: 2770
GUB cover: 13
Inf proof: 1
Zero half: 203
RLT: 109
Relax-and-lift: 301
Explored 29101 nodes (24314728 simplex iterations) in 2583.67 seconds
Thread count was 8 (of 8 available processors)
Solution count 10: 86623.5 86633 86759.8 ... 88012.3
Optimal solution found (tolerance 1.00e-04)
Best objective 8.662353516758e+04, best bound 8.661624837520e+04, gap 0.0084%So I tried to restore parameters to default,and change the objective function to see the result,the log file is something like,
Gurobi Optimizer version 9.1.0 build v9.1.0rc0 (win64)
Thread count: 4 physical cores, 8 logical processors, using up to 8 threads
Optimize a model with 27000 rows, 8679 columns and 72771 nonzeros
Model fingerprint: 0xca3429af
Variable types: 6540 continuous, 2139 integer (2139 binary)
Coefficient statistics:
Matrix range [7e-03, 2e+03]
Objective range [8e-01, 1e+00]
Bounds range [1e+00, 1e+00]
RHS range [9e-01, 6e+03]
Presolve removed 17072 rows and 5328 columns
Presolve time: 0.45s
Presolved: 9928 rows, 3351 columns, 39753 nonzeros
Variable types: 2280 continuous, 1071 integer (1043 binary)
Root relaxation: objective 1.102392e+05, 10222 iterations, 1.17 seconds
Nodes | Current Node | Objective Bounds | Work
Expl Unexpl | Obj Depth IntInf | Incumbent BestBd Gap | It/Node Time
0 0 110239.236 0 303 - 110239.236 - - 2s
0 0 110998.395 0 707 - 110998.395 - - 8s
[...]
H13339 511 113192.61319 113159.613 0.03% 1492 1623s
13582 351 113190.255 44 140 113192.613 113159.613 0.03% 1474 1637s
14502 126 113174.977 53 65 113192.613 113170.963 0.02% 1396 1646s
Cutting planes:
Learned: 54
Gomory: 1
Cover: 191
Implied bound: 338
Projected implied bound: 147
Clique: 76
MIR: 364
StrongCG: 2
Flow cover: 959
GUB cover: 11
Inf proof: 2
Zero half: 17
RLT: 49
Relax-and-lift: 105
Explored 15247 nodes (23648618 simplex iterations) in 1647.00 seconds
Thread count was 8 (of 8 available processors)
Solution count 10: 113193 113193 113200 ... 113348
Optimal solution found (tolerance 1.00e-04)
Best objective 1.131926131931e+05, best bound 1.131857704849e+05, gap 0.0060%I see the last log file has no gap value until 1174s and the solving time seems to be not improved.
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