求解器“CPLEX”失败。参数建议答案

【问题标题】：Solver 'CPLEX' failed. Suggestion of parameters求解器“CPLEX”失败。参数建议
【发布时间】：2020-04-14 12:36:20
【问题描述】：

我正在尝试使用 cplex 来解决 LP 优化问题。（在 python 中使用 cvxpy）

根据我对问题的约束，cplex 求解器有时无法找到解决方案。当提供verbose=True 时，我想要一些关于如何读取求解器输出的直觉。

例如，我得到这个：

Version identifier: 12.10.0.0 | 2019-11-26 | 843d4de
CPXPARAM_Read_DataCheck                          1
CPXPARAM_Preprocessing_QCPDuals                  2
Found incumbent of value 0.000000 after 0.00 sec. (0.08 ticks)
Tried aggregator 2 times.
MIP Presolve eliminated 4726 rows and 353 columns.
MIP Presolve modified 1008 coefficients.
Aggregator did 3 substitutions.
Reduced MIP has 1669 rows, 1670 columns, and 4505 nonzeros.
Reduced MIP has 1168 binaries, 0 generals, 0 SOSs, and 0 indicators.
Presolve time = 0.04 sec. (5.22 ticks)
Probing fixed 0 vars, tightened 2 bounds.
Probing time = 0.01 sec. (0.85 ticks)
Tried aggregator 1 time.
Detecting symmetries...
MIP Presolve modified 2 coefficients.
Reduced MIP has 1669 rows, 1670 columns, and 4505 nonzeros.
Reduced MIP has 1168 binaries, 0 generals, 0 SOSs, and 0 indicators.
Presolve time = 0.03 sec. (3.10 ticks)
Probing time = 0.01 sec. (0.90 ticks)
Clique table members: 2327.
MIP emphasis: balance optimality and feasibility.
MIP search method: dynamic search.
Parallel mode: deterministic, using up to 4 threads.
Root relaxation solution time = 0.01 sec. (5.82 ticks)

        Nodes                                         Cuts/
   Node  Left     Objective  IInf  Best Integer    Best Bound    ItCnt     Gap

*     0+    0                            0.0000  -325889.6000              --- 
      0     0   -23545.7611   333        0.0000   -23545.7611      723     --- 
*     0+    0                       -15240.4400   -23545.7611            54.50%
      0     0   -21360.6115   333   -15240.4400     Cuts: 333     1063   40.16%
*     0+    0                       -20698.8800   -21360.6115             3.20%
      0     0   -21120.8531   333   -20698.8800     Cuts: 268     1232    2.04%
*     0+    0                       -20751.6200   -21120.8531             1.78%
      0     0   -21057.6246   333   -20751.6200      Cuts: 92     1322    1.47%
*     0+    0                       -20843.7200   -21057.6246             1.03%
      0     0   -21023.5211   333   -20843.7200      Cuts: 90     1397    0.86%
      0     0   -20983.6905   333   -20843.7200      Cuts: 57     1440    0.67%
*     0+    0                       -20877.4400   -20983.6905             0.51%
Detecting symmetries...
      0     0   -20972.8355   333   -20877.4400      Cuts: 13     1449    0.46%
*     0+    0                       -20878.2600   -20972.8355             0.45%
      0     0   -20970.0341   333   -20878.2600      Cuts: 19     1460    0.44%
      0     0   -20969.6020   333   -20878.2600      Cuts: 10     1471    0.44%
      0     0   -20969.2988   333   -20878.2600    MIRcuts: 4     1476    0.44%
      0     0   -20959.2311   333   -20878.2600       Cuts: 9     1483    0.39%
*     0+    0                       -20935.7200   -20959.2311             0.11%
      0     0   -20958.0881   333   -20935.7200      Cuts: 15     1500    0.11%
*     0+    0                       -20935.7200   -20958.0881             0.11%
Detecting symmetries...

Repeating presolve.
Tried aggregator 2 times.
MIP Presolve eliminated 1039 rows and 925 columns.
MIP Presolve modified 62 coefficients.
Aggregator did 102 substitutions.
Reduced MIP has 528 rows, 639 columns, and 1468 nonzeros.
Reduced MIP has 526 binaries, 0 generals, 0 SOSs, and 0 indicators.
Presolve time = 0.04 sec. (2.78 ticks)
Probing fixed 0 vars, tightened 18 bounds.
Probing time = 0.00 sec. (0.36 ticks)
Tried aggregator 2 times.
MIP Presolve eliminated 241 rows and 308 columns.
MIP Presolve modified 23 coefficients.
Aggregator did 2 substitutions.
Reduced MIP has 285 rows, 329 columns, and 792 nonzeros.
Reduced MIP has 261 binaries, 0 generals, 0 SOSs, and 0 indicators.
Presolve time = 0.01 sec. (0.68 ticks)
Probing fixed 0 vars, tightened 1 bounds.
Probing time = 0.01 sec. (0.18 ticks)
Tried aggregator 1 time.
Detecting symmetries...
MIP Presolve modified 1 coefficients.
Reduced MIP has 285 rows, 329 columns, and 792 nonzeros.
Reduced MIP has 261 binaries, 0 generals, 0 SOSs, and 0 indicators.
Presolve time = 0.03 sec. (0.58 ticks)
Represolve time = 0.18 sec. (19.83 ticks)
Probing time = 0.00 sec. (0.18 ticks)
Clique table members: 547.
MIP emphasis: balance optimality and feasibility.
MIP search method: dynamic search.
Parallel mode: deterministic, using up to 4 threads.
Root relaxation solution time = 0.00 sec. (1.32 ticks)

        Nodes                                         Cuts/
   Node  Left     Objective  IInf  Best Integer    Best Bound    ItCnt     Gap

*     0+    0                       -20935.7200   -20949.2232             0.06%
      0     0   -20950.6138    31   -20935.7200   -20949.2232     1635    0.06%
      0     0   -20946.9943    31   -20935.7200      Cuts: 27     1650    0.05%
      0     0   -20946.9195    31   -20935.7200    MIRcuts: 4     1653    0.05%
      0     0   -20945.8979    31   -20935.7200      Cuts: 11     1658    0.05%
      0     0   -20945.8979    31   -20935.7200   Flowcuts: 2     1659    0.05%
      0     0   -20945.8979    31   -20935.7200   Flowcuts: 1     1663    0.05%
Detecting symmetries...

Clique cuts applied:  10
Implied bound cuts applied:  3
Flow cuts applied:  35
Mixed integer rounding cuts applied:  37
Lift and project cuts applied:  3
Gomory fractional cuts applied:  1

Root node processing (before b&c):
  Real time             =    1.34 sec. (232.86 ticks)
Parallel b&c, 4 threads:
  Real time             =    0.00 sec. (0.00 ticks)
  Sync time (average)   =    0.00 sec.
  Wait time (average)   =    0.00 sec.
                          ------------
Total (root+branch&cut) =    1.34 sec. (232.86 ticks)

从给定的运行。我从this 知道如何将参数通过 cvxpy 传递到 cplex，但是读取求解器的输出并不能帮助我确定求解器是否由于内存问题而失败，或数字问题或任何类似的问题，并因此调整参数。我还想指出，我使用的约束集很大（每个数据点可以达到 34 个），但求解器在非常小的数据帧（只有 24 个点）上仍然失败

有什么可以帮助我的建议/材料吗？

非常感谢！

【问题讨论】：

最简单的方法是将模型导出到文件（最好是 SAV），然后使用交互式 CPLEX 优化器进行调查。在那里您可以运行冲突优化器来查找冲突。
谢谢，我要试试 :)
你没有说求解器多久失败。它会很快失败，还是在（长时间）后失败？您从日志文件中得到什么 - 您在上面给出的摘录表明问题是可行的，并且求解器已经找到了解决方案。当求解器失败时，你没有得到任何日志吗？您能否发布更多关于求解器失败时会发生什么的信息。
它失败的速度相对较快（仅几秒钟），但从 ~/.virtualenvs/tomorrow/lib/python3.7/site-packages/cvxpy/problems/problem.py in unpack_results(self, solution, chain, inverse_data) 716 raise error.SolverError( 717 "Solver '%s' failed. " % chain.solver.name() + --> 718 "Try another solver, or solve with verbose=True for more " 719 "information.") 720 self.unpack(solution) 引发的异常由求解器返回状态 solver_error 触发

标签： python cplex cvxpy

【解决方案1】：

你可以使用状态。让我使用bus example。

# Import packages.
import cvxpy as cp


# Define and solve the CVXPY problem.
nbBus40 = cp.Variable(integer=True)
nbBus30 = cp.Variable( integer=True)
cost = 500*nbBus40+400*nbBus30
prob = cp.Problem(cp.Minimize(cost),[40*nbBus40+30*nbBus30>=300,
                                     nbBus40>=0,nbBus30>=0
                                     ])

prob.solve(solver=cp.CPLEX,verbose=True)

print("status = ",prob.status)

# Print result.
print("\nThe minimal cost is", prob.value)

print("number buses 40 seats = ",nbBus40.value)
print("number buses 30 seats = ",nbBus30.value)

给予

status =  optimal

The minimal cost is 3800.0
number buses 40 seats =  6.0
number buses 30 seats =  2.0

而如果我们将约束更改为

prob = cp.Problem(cp.Minimize(cost),[40*nbBus40+30*nbBus30>=300,
                                     nbBus40>=0,nbBus30>=0,nbBus40<=2,nbBus30<=2
                                     ])

然后我们得到

status =  infeasible

The minimal cost is inf
number buses 40 seats =  None
number buses 30 seats =  None

【讨论】：

感谢您的示例 Alex，但我无法访问状态，因为求解器在返回任何状态之前失败。我正在寻找的是一种有效的方法来调查导致求解器失败的原因，以及调整参数是否可以找到解决方案
然后尝试 prob.solve(solver=cp.CPLEX,verbose=True,cplex_filename="c://temp//cvx.sav") 以生成可以调试的 sav 文件交互式 cplex