Я изучаю C ++ API CBC, и у меня возникают проблемы с сопоставлением производительности скомпилированной программы C ++, которая загружает файл MPS и решает его с помощью класса CbcModel по сравнению с простым открытием утилиты командной строки CBC и импортом того же самого файл и использование solve
, Утилита cmd line решает MIP за 1 секунду, а программа C ++ не завершает <10 минут.
Я понял, что проблема в том, что когда я использую C ++ API, мне нужно явно настроить все параметры, и кажется, что параметры по умолчанию, используемые утилитой cmd line, довольно хорошо округлены для вашей средней модели MIP.
Есть ли список параметров по умолчанию для предварительного разрешения, эвристики и срезов, которые используются утилитой cmd line и которые мне следует активировать в моей программе на C ++, чтобы соответствовать производительности. Возможно, кто-то поиграл с этими параметрами и нашел хороший набор параметров эмпирически.
Программа на C ++:
int main ()
{
OsiClpSolverInterface solver1;
solver1.setLogLevel(0);
// Read in example model in MPS file format
// and assert that it is a clean model
int numMpsReadErrors = solver1.readMps("generic_mip.mps","");
assert(numMpsReadErrors==0);
// Pass the solver with the problem to be solved to CbcModel
CbcModel model(solver1);
model.setLogLevel(0);
// Add clique cut generator
CglClique clique_generator;
model.addCutGenerator(&clique_generator,-1, "Clique");
// Add rounding heuristic
CglMixedIntegerRounding mixedGen;
model.addCutGenerator(&mixedGen, -1, "Rounding");
model.setNumberThreads(4);
model.messageHandler()->setPrefix(false);
model.branchAndBound();const double * solution = model.bestSolution();
printf("Optimal value is %.2f", *solution);
return 0;
}
Рассматриваемая модель MIP может быть загружена с ВОТ. Оптимальное объективное значение: -771,2957.
Журнал утилиты командной строки Cbc, в котором указываются все виды расширенных функций (предварительная обработка, первичная эвристика и сильное ветвление):
Continuous objective value is -798.689 - 0.03 seconds
Cgl0002I 21 variables fixed
Cgl0003I 0 fixed, 175 tightened bounds, 1972 strengthened rows, 0 substitutions
Cgl0004I processed model has 3731 rows, 3835 columns (3835 integer (3660 of which binary)) and 37873 elements
Cbc0038I Initial state - 365 integers unsatisfied sum - 129.125
Cbc0038I Pass 1: (0.18 seconds) suminf. 58.66667 (121) obj. -572.133 iterations 510
Cbc0038I Pass 2: (0.18 seconds) suminf. 58.66667 (121) obj. -572.133 iterations 23
Cbc0038I Pass 3: (0.18 seconds) suminf. 58.66667 (121) obj. -572.133 iterations 1
Cbc0038I Pass 4: (0.20 seconds) suminf. 69.00000 (138) obj. -299.496 iterations 589
Cbc0038I Pass 5: (0.20 seconds) suminf. 54.00000 (109) obj. -287.063 iterations 194
Cbc0038I Pass 6: (0.21 seconds) suminf. 54.00000 (109) obj. -287.063 iterations 12
Cbc0038I Pass 7: (0.21 seconds) suminf. 49.00000 (100) obj. -273.321 iterations 33
Cbc0038I Pass 8: (0.22 seconds) suminf. 48.00000 (97) obj. -269.421 iterations 14
Cbc0038I Pass 9: (0.22 seconds) suminf. 48.00000 (98) obj. -268.624 iterations 8
Cbc0038I Pass 10: (0.23 seconds) suminf. 48.00000 (97) obj. -264.813 iterations 4
Cbc0038I Pass 11: (0.23 seconds) suminf. 47.00000 (94) obj. -261.75 iterations 8
Cbc0038I Pass 12: (0.24 seconds) suminf. 47.00000 (94) obj. -261.75 iterations 3
Cbc0038I Pass 13: (0.24 seconds) suminf. 47.00000 (94) obj. -261.75 iterations 3
Cbc0038I Pass 14: (0.25 seconds) suminf. 57.75000 (118) obj. -103.115 iterations 508
Cbc0038I Pass 15: (0.26 seconds) suminf. 49.00000 (98) obj. -97.4793 iterations 163
Cbc0038I Pass 16: (0.26 seconds) suminf. 49.00000 (98) obj. -97.4793 iterations 3
Cbc0038I Pass 17: (0.27 seconds) suminf. 48.75000 (98) obj. -101.421 iterations 24
Cbc0038I Pass 18: (0.27 seconds) suminf. 47.00000 (94) obj. -103.346 iterations 25
Cbc0038I Pass 19: (0.28 seconds) suminf. 47.00000 (94) obj. -103.346 iterations 2
Cbc0038I Pass 20: (0.28 seconds) suminf. 47.00000 (94) obj. -103.346 iterations 21
Cbc0038I Pass 21: (0.29 seconds) suminf. 51.50000 (107) obj. 60.0315 iterations 469
Cbc0038I Pass 22: (0.30 seconds) suminf. 40.00000 (80) obj. 59.913 iterations 168
Cbc0038I Pass 23: (0.30 seconds) suminf. 40.00000 (80) obj. 59.913 iterations 2
Cbc0038I Pass 24: (0.31 seconds) suminf. 39.50000 (79) obj. 59.913 iterations 27
Cbc0038I Pass 25: (0.31 seconds) suminf. 39.00000 (78) obj. 59.913 iterations 23
Cbc0038I Pass 26: (0.32 seconds) suminf. 39.00000 (78) obj. 59.913 iterations 13
Cbc0038I Pass 27: (0.33 seconds) suminf. 50.00000 (101) obj. 124.699 iterations 504
Cbc0038I Pass 28: (0.34 seconds) suminf. 41.00000 (82) obj. 118.624 iterations 174
Cbc0038I Pass 29: (0.34 seconds) suminf. 41.00000 (82) obj. 118.624 iterations 5
Cbc0038I Pass 30: (0.34 seconds) suminf. 41.00000 (82) obj. 118.624 iterations 19
Cbc0038I No solution found this major pass
Cbc0038I Before mini branch and bound, 2356 integers at bound fixed and 0 continuous
Cbc0038I Mini branch and bound did not improve solution (0.41 seconds)
Cbc0038I After 0.41 seconds - Feasibility pump exiting - took 0.25 seconds
Cbc0031I 583 added rows had average density of 8.2024014
Cbc0013I At root node, 583 cuts changed objective from -798.68913 to -771.29565 in 10 passes
Cbc0014I Cut generator 0 (Probing) - 541 row cuts average 2.0 elements, 0 column cuts (0 active) in 0.044 seconds - new frequency is 1
Cbc0014I Cut generator 1 (Gomory) - 751 row cuts average 116.6 elements, 0 column cuts (0 active) in 0.108 seconds - new frequency is 1
Cbc0014I Cut generator 2 (Knapsack) - 451 row cuts average 2.0 elements, 0 column cuts (0 active) in 0.040 seconds - new frequency is 1
Cbc0014I Cut generator 3 (Clique) - 0 row cuts average 0.0 elements, 0 column cuts (0 active) in 0.004 seconds - new frequency is -100
Cbc0014I Cut generator 4 (MixedIntegerRounding2) - 155 row cuts average 16.9 elements, 0 column cuts (0 active) in 0.028 seconds - new frequency is 1
Cbc0014I Cut generator 5 (FlowCover) - 0 row cuts average 0.0 elements, 0 column cuts (0 active) in 0.008 seconds - new frequency is -100
Cbc0014I Cut generator 6 (TwoMirCuts) - 1171 row cuts average 20.0 elements, 0 column cuts (0 active) in 0.068 seconds - new frequency is 1
Cbc0010I After 0 nodes, 1 on tree, 1e+50 best solution, best possible -771.29565 (1.18 seconds)
Cbc0004I Integer solution of -771.29565 found after 2671 iterations and 1 nodes (1.24 seconds)
Cbc0001I Search completed - best objective -771.2956521739131, took 2671 iterations and 1 nodes (1.24 seconds)
Cbc0032I Strong branching done 22 times (542 iterations), fathomed 0 nodes and fixed 0 variables
Cbc0035I Maximum depth 0, 0 variables fixed on reduced cost
Cuts at root node changed objective from -798.689 to -771.296
Probing was tried 12 times and created 552 cuts of which 0 were active after adding rounds of cuts (0.044 seconds)
Gomory was tried 12 times and created 756 cuts of which 0 were active after adding rounds of cuts (0.116 seconds)
Knapsack was tried 12 times and created 456 cuts of which 0 were active after adding rounds of cuts (0.044 seconds)
Clique was tried 10 times and created 0 cuts of which 0 were active after adding rounds of cuts (0.004 seconds)
MixedIntegerRounding2 was tried 12 times and created 155 cuts of which 0 were active after adding rounds of cuts (0.036 seconds)
FlowCover was tried 10 times and created 0 cuts of which 0 were active after adding rounds of cuts (0.008 seconds)
TwoMirCuts was tried 12 times and created 1197 cuts of which 0 were active after adding rounds of cuts (0.084 seconds)
ImplicationCuts was tried 2 times and created 11 cuts of which 0 were active after adding rounds of cuts (0.000 seconds)
Result - Optimal solution found
Objective value: -771.29565217
Enumerated nodes: 1
Total iterations: 2671
Time (CPU seconds): 1.27
Time (Wallclock seconds): 1.30
Может быть эта часть официального кода помогает. Это линедок называется Set up likely cut generators and defaults
Код Си-би-си трудно читать, и трудно проанализировать, какое поведение по умолчанию существует, не тратя некоторое время.
Но приведенный выше код выглядит немного как настройки по умолчанию, активированные в некоторых вызовах cmd.
Какой компилятор вы используете?
Отладка включена или соотв. оптимизация отключена?
Например. для Visual Studio это имеет огромное значение для производительности и может быть причиной того, что ваш скомпилированный код работает намного медленнее.