[SCIP] About using SCIP to solve a MINLP problem

Mon Aug 3 12:08:50 CEST 2020

Thank you for your patience. I am a student. I am using SCIP to solve a MINLP problem. This is my model:
[cid:image001.png at 01D669BE.EA6C30F0]

bl is a binary variable, z is an element of the Zr matrix, Zr can be calculated, but the composition of Zr is very complicated; a is an element of matrix A, this constraint can be understood as A is the inverse of Zr, A* Zr=1; So in fact Z is linear, and A is also linear, which is equivalent to bilinear; both theta and epsilon are set parameters, and specific values can be calculated;
Here is a simple example, we set nq=2，nz=1，ntp=4；
Zr=[3.64545486 3.85360847 2.21292579 3.55129215
2.44837376 3.25989972 2.88290441 2.19697746]
We use AMPL to model, the model and data are as follows M1.mod  and M1.us;
In this small example, scip can quickly find the optimal solution, but when the scale of our problem expands, scip sometimes spends a lot of time finding the optimal solution, such as:

4.0s| 1 | 0 | 1 | - | 3700k | 0 | 156 | 10 | 29 | 0 | 0 | 0 | 0 | 3.000000e+00 | -- | Inf | unknown

4.0s| 1 | 0 | 3 | - | 3729k | 0 | 156 | 11 | 31 | 2 | 1 | 0 | 0 | 3.000000e+00 | -- | Inf | unknown

4.0s| 1 | 0 | 5 | - | 3892k | 0 | 156 | 11 | 32 | 3 | 2 | 0 | 0 | 3.000000e+00 | -- | Inf | unknown

4.0s| 1 | 0 | 7 | - | 3892k | 0 | 156 | 11 | 33 | 4 | 3 | 0 | 0 | 3.000000e+00 | -- | Inf | unknown

4.0s| 1 | 0 | 8 | - | 3896k | 0 | 156 | 11 | 34 | 5 | 4 | 0 | 0 | 3.000000e+00 | -- | Inf | unknown

4.0s| 1 | 0 | 9 | - | 3899k | 0 | 156 | 11 | 35 | 6 | 5 | 0 | 0 | 3.000000e+00 | -- | Inf | unknown

4.0s| 1 | 0 | 10 | - | 3994k | 0 | 156 | 11 | 36 | 7 | 6 | 0 | 0 | 3.000000e+00 | -- | Inf | unknown

4.0s| 1 | 0 | 13 | - | 3998k | 0 | 156 | 11 | 37 | 8 | 7 | 0 | 0 | 3.000000e+00 | -- | Inf | unknown

4.0s| 1 | 0 | 14 | - | 4001k | 0 | 156 | 11 | 38 | 9 | 8 | 0 | 0 | 3.000000e+00 | -- | Inf | unknown

4.0s| 1 | 0 | 15 | - | 4004k | 0 | 156 | 11 | 39 | 10 | 9 | 0 | 0 | 3.000000e+00 | -- | Inf | unknown

4.0s| 1 | 0 | 16 | - | 4008k | 0 | 156 | 11 | 40 | 11 | 10 | 0 | 0 | 3.000000e+00 | -- | Inf | unknown

4.0s| 1 | 0 | 17 | - | 4012k | 0 | 156 | 11 | 11 | 12 | 11 | 0 | 0 | 3.000000e+00 | -- | Inf | unknown

4.0s| 1 | 0 | 20 | - | 4013k | 0 | 156 | 11 | 12 | 13 | 12 | 0 | 0 | 3.000000e+00 | -- | Inf | unknown

******************************************************************************

This program contains Ipopt, a library for large-scale nonlinear optimization.

Ipopt is released as open source code under the Eclipse Public License (EPL).

For more information visit http://projects.coin-or.org/Ipopt

******************************************************************************

5.0s| 1 | 0 | 27 | - | 4228k | 0 | 156 | 13 | 21 | 22 | 12 | 0 | 0 | 3.000000e+00 | -- | Inf | unknown

5.0s| 1 | 0 | 30 | - | 4228k | 0 | 156 | 13 | 19 | 23 | 13 | 0 | 0 | 3.000000e+00 | -- | Inf | unknown

5.0s| 1 | 2 | 30 | - | 4228k | 0 | 156 | 13 | 19 | 23 | 14 | 0 | 2 | 3.000000e+00 | -- | Inf | unknown

r 5.0s| 7 | 7 | 301 | 45.8 |rounding| 6 | 156 | 18 | 51 | 112 | 4 | 0 | 4 | 3.000000e+00 | 7.000000e+00 | 133.33%| 0.29%

r 7.0s| 29 | 26 | 649 | 22.3 |rounding| 21 | 156 | 18 | 58 | 205 | 4 | 0 | 14 | 3.000000e+00 | 5.000000e+00 | 66.67%| 1.15%

d10.0s| 71 | 13 | 1070 | 14.9 |nlpdivin| 23 | 156 | 18 | 25 | 291 | 1 | 0 | 14 | 3.000000e+00 | 4.000000e+00 | 33.33%| 23.92%

10.0s| 100 | 24 | 1351 | 13.4 | 5979k | 23 | 156 | 18 | 49 | 437 | 3 | 0 | 15 | 3.000000e+00 | 4.000000e+00 | 33.33%| 24.49%

12.0s| 200 | 24 | 2393 | 11.9 | 6636k | 65 | 156 | 18 | 122 |1046 | 3 | 0 | 23 | 3.000000e+00 | 4.000000e+00 | 33.33%| 24.49%

13.0s| 300 | 24 | 3251 | 10.8 | 7738k | 115 | 156 | 18 | 222 |1696 | 3 | 0 | 23 | 3.000000e+00 | 4.000000e+00 | 33.33%| 24.49%

14.0s| 400 | 54 | 4154 | 10.3 | 8345k | 143 | 156 | 18 | 124 |2340 | 2 | 0 | 23 | 3.000000e+00 | 4.000000e+00 | 33.33%| 24.49%

15.0s| 500 | 54 | 5352 | 10.7 | 8964k | 143 | 156 | 18 | 234 |3043 | 2 | 0 | 23 | 3.000000e+00 | 4.000000e+00 | 33.33%| 24.49%

16.0s| 600 | 90 | 6299 | 10.5 | 10M | 143 | 156 | 18 | 110 |3561 | 2 | 0 | 25 | 3.000000e+00 | 4.000000e+00 | 33.33%| 26.78%

17.0s| 700 | 162 | 7015 | 10.0 | 12M | 143 | 156 | 18 | 72 |3963 | 2 | 0 | 34 | 3.000000e+00 | 4.000000e+00 | 33.33%| 27.93%

18.0s| 800 | 236 | 7630 | 9.5 | 12M | 143 | 156 | 18 | 94 |4311 | 2 | 0 | 46 | 3.000000e+00 | 4.000000e+00 | 33.33%| 28.50%

20.0s| 900 | 310 | 8387 | 9.3 | 14M | 143 | 156 | 18 | 22 |4659 | 2 | 0 | 61 | 3.000000e+00 | 4.000000e+00 | 33.33%| 28.79%

21.0s| 1000 | 340 | 9725 | 9.7 | 16M | 143 | 156 | 18 | 182 |5253 | 2 | 0 | 71 | 3.000000e+00 | 4.000000e+00 | 33.33%| 28.93%

22.0s| 1100 | 414 | 10609 | 9.6 | 18M | 143 | 156 | 18 | 147 |5696 | 2 | 0 | 92 | 3.000000e+00 | 4.000000e+00 | 33.33%| 29.00%

24.0s| 1200 | 450 | 11828 | 9.8 | 20M | 143 | 156 | 18 | 144 |6247 | 2 | 0 | 107 | 3.000000e+00 | 4.000000e+00 | 33.33%| 29.04%

25.0s| 1300 | 490 | 13189 | 10.1 | 21M | 143 | 156 | 18 | 96 |6775 | 2 | 0 | 121 | 3.000000e+00 | 4.000000e+00 | 33.33%| 29.05%

26.0s| 1400 | 490 | 14129 | 10.1 | 21M | 143 | 156 | 18 | 147 |7326 | 2 | 0 | 121 | 3.000000e+00 | 4.000000e+00 | 33.33%| 29.05%

26.0s| 1500 | 508 | 14955 | 10.0 | 23M | 144 | 156 | 18 | 234 |7747 | 2 | 0 | 121 | 3.000000e+00 | 4.000000e+00 | 33.33%| 29.05%

27.0s| 1600 | 550 | 16127 | 10.1 | 23M | 144 | 156 | 18 | 254 |8241 | 2 | 0 | 121 | 3.000000e+00 | 4.000000e+00 | 33.33%| 29.05%

28.0s| 1700 | 594 | 17362 | 10.2 | 25M | 144 | 156 | 18 | 181 |8685 | 2 | 0 | 121 | 3.000000e+00 | 4.000000e+00 | 33.33%| 29.05%

29.0s| 1800 | 612 | 20188 | 11.2 | 25M | 144 | 156 | 18 | 341 |9373 | 2 | 0 | 126 | 3.000000e+00 | 4.000000e+00 | 33.33%| 29.05%

30.0s| 1900 | 646 | 21011 | 11.1 | 27M | 144 | 156 | 18 | 128 |9955 | 3 | 0 | 133 | 3.000000e+00 | 4.000000e+00 | 33.33%| 29.05%

30.0s| 2000 | 662 | 22015 | 11.0 | 27M | 144 | 156 | 18 | 228 | 10k| 2 | 0 | 139 | 3.000000e+00 | 4.000000e+00 | 33.33%| 29.05%

31.0s| 2100 | 666 | 23205 | 11.0 | 28M | 144 | 156 | 18 | 184 | 11k| 2 | 0 | 144 | 3.000000e+00 | 4.000000e+00 | 33.33%| 29.05%

32.0s| 2200 | 662 | 25329 | 11.5 | 28M | 149 | 156 | 18 | 346 | 12k| 2 | 0 | 144 | 3.000000e+00 | 4.000000e+00 | 33.33%| 29.05%

33.0s| 2300 | 656 | 27038 | 11.7 | 28M | 149 | 156 | 18 | 52 | 12k| 2 | 0 | 145 | 3.000000e+00 | 4.000000e+00 | 33.33%| 33.64%

34.0s| 2400 | 656 | 28141 | 11.7 | 28M | 149 | 156 | 18 | 125 | 13k| 3 | 0 | 145 | 3.000000e+00 | 4.000000e+00 | 33.33%| 33.64%

34.0s| 2500 | 656 | 29170 | 11.7 | 28M | 149 | 156 | 18 | 176 | 13k| 3 | 0 | 145 | 3.000000e+00 | 4.000000e+00 | 33.33%| 33.64%

35.0s| 2600 | 658 | 30550 | 11.7 | 28M | 149 | 156 | 18 | 28 | 14k| 1 | 0 | 145 | 3.000000e+00 | 4.000000e+00 | 33.33%| 35.93%

36.0s| 2700 | 658 | 31593 | 11.7 | 28M | 149 | 156 | 18 | 28 | 15k| 1 | 0 | 145 | 3.000000e+00 | 4.000000e+00 | 33.33%| 35.93%

36.0s| 2800 | 658 | 32449 | 11.6 | 28M | 149 | 156 | 18 | 28 | 15k| 1 | 0 | 145 | 3.000000e+00 | 4.000000e+00 | 33.33%| 35.93%

37.0s| 2900 | 660 | 33411 | 11.5 | 28M | 149 | 156 | 18 | 39 | 16k| 3 | 0 | 146 | 3.000000e+00 | 4.000000e+00 | 33.33%| 37.08%

38.0s| 3000 | 660 | 34321 | 11.4 | 28M | 149 | 156 | 18 | 39 | 16k| 3 | 0 | 146 | 3.000000e+00 | 4.000000e+00 | 33.33%| 37.08%

38.0s| 3100 | 660 | 35265 | 11.4 | 28M | 149 | 156 | 18 | 39 | 17k| 3 | 0 | 146 | 3.000000e+00 | 4.000000e+00 | 33.33%| 37.08%

39.0s| 3200 | 662 | 36354 | 11.4 | 28M | 149 | 156 | 18 | 43 | 17k| 3 | 0 | 147 | 3.000000e+00 | 4.000000e+00 | 33.33%| 37.65%

40.0s| 3300 | 662 | 37378 | 11.3 | 28M | 149 | 156 | 18 | 43 | 18k| 3 | 0 | 147 | 3.000000e+00 | 4.000000e+00 | 33.33%| 37.65%

40.0s| 3400 | 666 | 38304 | 11.3 | 28M | 149 | 156 | 18 | 31 | 18k| 2 | 0 | 147 | 3.000000e+00 | 4.000000e+00 | 33.33%| 37.79%

41.0s| 3500 | 666 | 39331 | 11.2 | 28M | 149 | 156 | 18 | 31 | 19k| 1 | 0 | 147 | 3.000000e+00 | 4.000000e+00 | 33.33%| 37.94%

42.0s| 3600 | 666 | 40398 | 11.2 | 28M | 149 | 156 | 18 | 31 | 20k| 1 | 0 | 147 | 3.000000e+00 | 4.000000e+00 | 33.33%| 37.94%

43.0s| 3700 | 668 | 41433 | 11.2 | 28M | 149 | 156 | 18 | 44 | 20k| 3 | 0 | 147 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.08%

43.0s| 3800 | 668 | 42458 | 11.2 | 28M | 149 | 156 | 18 | 44 | 21k| 3 | 0 | 147 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.08%

44.0s| 3900 | 668 | 43553 | 11.2 | 28M | 149 | 156 | 18 | 48 | 21k| 3 | 0 | 147 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.08%

45.0s| 4000 | 670 | 44720 | 11.2 | 28M | 149 | 156 | 18 | 51 | 22k| 3 | 0 | 148 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.15%

45.0s| 4100 | 670 | 45986 | 11.2 | 28M | 149 | 156 | 18 | 54 | 23k| 3 | 0 | 148 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.15%

46.0s| 4200 | 670 | 47087 | 11.2 | 28M | 149 | 156 | 18 | 49 | 23k| 3 | 0 | 148 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.15%

47.0s| 4300 | 672 | 48328 | 11.2 | 28M | 149 | 156 | 18 | 37 | 24k| 1 | 0 | 149 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.19%

47.0s| 4400 | 672 | 49605 | 11.3 | 28M | 149 | 156 | 18 | 39 | 25k| 1 | 0 | 149 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.19%

48.0s| 4500 | 672 | 50695 | 11.3 | 28M | 149 | 156 | 18 | 48 | 25k| 3 | 0 | 149 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.20%

49.0s| 4600 | 672 | 51925 | 11.3 | 28M | 149 | 156 | 18 | 48 | 26k| 3 | 0 | 149 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.20%

49.0s| 4700 | 672 | 53120 | 11.3 | 28M | 149 | 156 | 18 | 49 | 26k| 3 | 0 | 149 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.20%

50.0s| 4800 | 674 | 54467 | 11.3 | 28M | 149 | 156 | 18 | 56 | 27k| 3 | 0 | 149 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.21%

51.0s| 4900 | 674 | 55967 | 11.4 | 29M | 149 | 156 | 18 | 56 | 28k| 3 | 0 | 149 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.21%

52.0s| 5000 | 674 | 56922 | 11.4 | 29M | 149 | 156 | 18 | 52 | 28k| 3 | 0 | 149 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.21%

52.0s| 5100 | 678 | 57987 | 11.4 | 29M | 149 | 156 | 18 | 45 | 29k| 1 | 0 | 150 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.22%

53.0s| 5200 | 678 | 59000 | 11.3 | 29M | 149 | 156 | 18 | 45 | 29k| 1 | 0 | 150 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.22%

54.0s| 5300 | 678 | 60023 | 11.3 | 29M | 149 | 156 | 18 | 60 | 30k| 3 | 0 | 151 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.22%

54.0s| 5400 | 678 | 61132 | 11.3 | 29M | 149 | 156 | 18 | 60 | 30k| 3 | 0 | 151 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.22%

55.0s| 5500 | 678 | 62193 | 11.3 | 29M | 149 | 156 | 18 | 60 | 31k| 3 | 0 | 151 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.22%

56.0s| 5600 | 680 | 63284 | 11.3 | 29M | 149 | 156 | 18 | 50 | 31k| 1 | 0 | 151 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.22%

56.0s| 5700 | 680 | 64457 | 11.3 | 29M | 149 | 156 | 18 | 50 | 32k| 1 | 0 | 151 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.22%

57.0s| 5800 | 680 | 65597 | 11.3 | 29M | 149 | 156 | 18 | 50 | 33k| 1 | 0 | 151 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.22%

58.0s| 5900 | 680 | 66775 | 11.3 | 29M | 149 | 156 | 18 | 62 | 33k| 3 | 0 | 151 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.22%

58.0s| 6000 | 680 | 67907 | 11.3 | 29M | 149 | 156 | 18 | 62 | 34k| 3 | 0 | 151 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.22%

59.0s| 6100 | 684 | 69117 | 11.3 | 31M | 149 | 156 | 18 | 59 | 34k| 1 | 0 | 152 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.22%

60.0s| 6200 | 684 | 70320 | 11.3 | 31M | 149 | 156 | 18 | 59 | 35k| 1 | 0 | 152 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.22%

60.0s| 6300 | 684 | 71343 | 11.3 | 31M | 149 | 156 | 18 | 59 | 35k| 1 | 0 | 152 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.22%

61.0s| 6400 | 684 | 72784 | 11.4 | 31M | 149 | 156 | 18 | 67 | 36k| 3 | 0 | 152 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.22%

62.0s| 6500 | 684 | 74011 | 11.4 | 31M | 149 | 156 | 18 | 67 | 36k| 3 | 0 | 152 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.22%

63.0s| 6600 | 686 | 75062 | 11.4 | 31M | 149 | 156 | 18 | 70 | 37k| 3 | 0 | 153 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.22%

63.0s| 6700 | 686 | 76130 | 11.4 | 31M | 149 | 156 | 18 | 70 | 38k| 3 | 0 | 153 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.22%

64.0s| 6800 | 686 | 77023 | 11.3 | 31M | 149 | 156 | 18 | 68 | 38k| 2 | 0 | 153 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.22%

65.0s| 6900 | 688 | 78183 | 11.3 | 31M | 149 | 156 | 18 | 61 | 39k| 1 | 0 | 153 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.22%

65.0s| 7000 | 688 | 79338 | 11.3 | 31M | 149 | 156 | 18 | 61 | 39k| 1 | 0 | 153 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.22%

66.0s| 7100 | 690 | 80535 | 11.3 | 31M | 149 | 156 | 18 | 76 | 40k| 3 | 0 | 154 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.22%

67.0s| 7200 | 690 | 81803 | 11.4 | 31M | 149 | 156 | 18 | 116 | 40k| 3 | 0 | 154 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.22%

67.0s| 7300 | 690 | 82707 | 11.3 | 31M | 149 | 156 | 18 | 117 | 41k| 3 | 0 | 154 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.22%

68.0s| 7400 | 694 | 83671 | 11.3 | 31M | 149 | 156 | 18 | 62 | 41k| 1 | 0 | 155 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.22%

69.0s| 7500 | 694 | 84489 | 11.3 | 31M | 149 | 156 | 18 | 63 | 42k| 1 | 0 | 155 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.22%

69.0s| 7600 | 696 | 85576 | 11.3 | 31M | 149 | 156 | 18 | 76 | 43k| 3 | 0 | 155 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.22%

70.0s| 7700 | 696 | 86825 | 11.3 | 31M | 149 | 156 | 18 | 80 | 43k| 3 | 0 | 155 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.22%

71.0s| 7800 | 696 | 87893 | 11.3 | 31M | 149 | 156 | 18 | 80 | 44k| 3 | 0 | 155 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.22%

72.0s| 7900 | 698 | 88866 | 11.2 | 33M | 149 | 156 | 18 | 65 | 44k| 1 | 0 | 155 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.22%

72.0s| 8000 | 698 | 89659 | 11.2 | 33M | 149 | 156 | 18 | 66 | 45k| 1 | 0 | 155 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.22%

73.0s| 8100 | 700 | 90468 | 11.2 | 33M | 149 | 156 | 18 | 78 | 45k| 3 | 0 | 156 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.22%

74.0s| 8200 | 700 | 91324 | 11.1 | 33M | 149 | 156 | 18 | 83 | 46k| 3 | 0 | 156 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.22%

74.0s| 8300 | 702 | 92294 | 11.1 | 33M | 149 | 156 | 18 | 83 | 46k| 3 | 0 | 156 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.22%

75.0s| 8400 | 702 | 93181 | 11.1 | 33M | 149 | 156 | 18 | 82 | 47k| 3 | 0 | 190 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.22%

76.0s| 8500 | 702 | 94139 | 11.1 | 33M | 149 | 156 | 18 | 82 | 48k| 3 | 0 | 198 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.22%

77.0s| 8600 | 704 | 95255 | 11.1 | 34M | 149 | 156 | 18 | 86 | 48k| 3 | 0 | 200 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.22%

78.0s| 8700 | 704 | 96224 | 11.1 | 34M | 149 | 156 | 18 | 86 | 49k| 3 | 0 | 200 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.22%

78.0s| 8800 | 706 | 97230 | 11.0 | 34M | 149 | 156 | 18 | 76 | 49k| 1 | 0 | 200 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.22%

79.0s| 8900 | 706 | 98053 | 11.0 | 34M | 149 | 156 | 18 | 76 | 50k| 1 | 0 | 224 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.22%

80.0s| 9000 | 706 | 99030 | 11.0 | 34M | 149 | 156 | 18 | 86 | 50k| 3 | 0 | 224 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.22%

81.0s| 9100 | 706 | 99830 | 11.0 | 35M | 149 | 156 | 18 | 86 | 51k| 3 | 0 | 224 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.22%

81.0s| 9200 | 706 |100740 | 10.9 | 35M | 149 | 156 | 18 | 87 | 52k| 3 | 0 | 224 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.22%

82.0s| 9300 | 710 |101768 | 10.9 | 35M | 149 | 156 | 18 | 76 | 52k| 1 | 0 | 224 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.22%

83.0s| 9400 | 710 |102664 | 10.9 | 35M | 149 | 156 | 18 | 77 | 53k| 1 | 0 | 224 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.22%

83.0s| 9500 | 712 |103630 | 10.9 | 35M | 149 | 156 | 18 | 91 | 53k| 3 | 0 | 224 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.22%

84.0s| 9600 | 712 |104370 | 10.9 | 35M | 149 | 156 | 18 | 89 | 54k| 2 | 0 | 224 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.22%

85.0s| 9700 | 714 |105400 | 10.9 | 35M | 149 | 156 | 18 | 79 | 54k| 1 | 0 | 224 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.22%

86.0s| 9800 | 714 |106416 | 10.9 | 35M | 149 | 156 | 18 | 79 | 55k| 1 | 0 | 224 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.22%

86.0s| 9900 | 714 |107245 | 10.8 | 35M | 149 | 156 | 18 | 80 | 56k| 1 | 0 | 224 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.22%

87.0s| 10000 | 716 |108308 | 10.8 | 36M | 149 | 156 | 18 | 91 | 56k| 3 | 0 | 224 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.22%

88.0s| 10100 | 716 |109126 | 10.8 | 36M | 149 | 156 | 18 | 90 | 57k| 2 | 0 | 224 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.22%

88.0s| 10200 | 720 |110163 | 10.8 | 36M | 149 | 156 | 18 | 81 | 57k| 1 | 0 | 224 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.22%

89.0s| 10300 | 720 |111050 | 10.8 | 36M | 149 | 156 | 18 | 82 | 58k| 1 | 0 | 224 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.22%

90.0s| 10400 | 722 |112029 | 10.8 | 36M | 149 | 156 | 18 | 93 | 58k| 3 | 0 | 224 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.22%

90.0s| 10500 | 722 |112977 | 10.8 | 36M | 149 | 156 | 18 | 94 | 59k| 3 | 0 | 224 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.22%

91.0s| 10600 | 726 |113957 | 10.7 | 36M | 149 | 156 | 18 | 86 | 59k| 1 | 0 | 225 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.22%

92.0s| 10700 | 726 |115069 | 10.8 | 36M | 149 | 156 | 18 | 89 | 60k| 1 | 0 | 225 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.22%

92.0s| 10800 | 728 |116011 | 10.7 | 37M | 149 | 156 | 18 | 99 | 60k| 3 | 0 | 225 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.22%

93.0s| 10900 | 728 |117107 | 10.7 | 37M | 149 | 156 | 18 | 103 | 61k| 3 | 0 | 225 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.22%

94.0s| 11000 | 730 |118218 | 10.7 | 37M | 149 | 156 | 18 | 103 | 62k| 3 | 0 | 226 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.22%

94.0s| 11100 | 730 |119418 | 10.8 | 37M | 149 | 156 | 18 | 106 | 62k| 3 | 0 | 226 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.22%

95.0s| 11200 | 730 |120532 | 10.8 | 37M | 149 | 156 | 18 | 109 | 63k| 3 | 0 | 226 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.22%

96.0s| 11300 | 734 |121727 | 10.8 | 37M | 149 | 156 | 18 | 95 | 63k| 1 | 0 | 226 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.22%

97.0s| 11400 | 734 |122717 | 10.8 | 37M | 149 | 156 | 18 | 95 | 64k| 1 | 0 | 226 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.22%

97.0s| 11500 | 734 |123765 | 10.8 | 37M | 149 | 156 | 18 | 103 | 64k| 3 | 0 | 226 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.22%

98.0s| 11600 | 734 |124795 | 10.8 | 37M | 149 | 156 | 18 | 108 | 65k| 3 | 0 | 226 | 3.000000e+00 | 4.000000e+00 | 33.33%| 38.22%

*98.0s| 11622 | 0 |125035 | 10.8 | LP | 149 | 156 | 18 | 106 | 65k| 3 | 0 | 226 | 3.000000e+00 | 3.000000e+00 | 0.00%| 100.00%
I want to make SCIP calculation faster, can it be achieved by changing the parameters?
And can I speed up the calculation of SCIP through a good initialization strategy?
Best,
Jax

?送自 Windows 10 版?件<https://go.microsoft.com/fwlink/?LinkId=550986>?用

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