Cplex给出了解决方案状态= 6，这意味着我的概率没有最佳解决方案？

Question

我已经在Cplex上运行了我的解决方案，并得到了下面的结果。它最后以星号（*）字符进行了很多迭代。我打印了解决方案状态= 6。这是否意味着我的问题无法达到最佳效果，并且我得到的变量不能准确？

Tried aggregator 1 time. 
QP Presolve eliminated 1070 rows and 7712 columns. 
Aggregator did 1 substitutions. 
Reduced QP has 19229 rows, 11762 columns, and 70837 nonzeros. 
Reduced QP objective Q matrix has 9999 nonzeros. 
Presolve time = 0.06 sec. (15.71 ticks) 
Parallel mode: using up to 4 threads for barrier. 

***NOTE: Found 185 dense columns. 

Number of nonzeros in lower triangle of A*A' = 237322 
Using Nested Dissection ordering 
Total time for automatic ordering = 0.51 sec. (186.51 ticks) 
Summary statistics for Cholesky factor: 
    Threads     = 4 
    Rows in Factor   = 19414 
    Integer space required = 84705 
    Total non-zeros in factor = 1315542 
    Total FP ops to factor = 377093574 
Itn  Primal Obj  Dual Obj Prim Inf Upper Inf Dual Inf 
    0 2.1556826e+024 -2.1556826e+024 2.90e+016 0.00e+000 4.15e+012 
    1 2.8969373e+022 -2.8969375e+022 3.37e+015 0.00e+000 4.82e+011 
    2 6.6438243e+021 -6.6438260e+021 1.61e+015 0.00e+000 2.31e+011 
    3 1.5738876e+021 -1.5738892e+021 7.85e+014 0.00e+000 1.12e+011 
    4 8.7363163e+020 -8.7363321e+020 5.85e+014 0.00e+000 8.36e+010 
    5 5.6810167e+020 -5.6810318e+020 4.72e+014 0.00e+000 6.74e+010 
    6 1.3407969e+020 -1.3408088e+020 2.29e+014 0.00e+000 3.28e+010 
    7 2.6178239e+019 -2.6178999e+019 1.01e+014 0.00e+000 1.45e+010 
    8 1.5196152e+018 -1.5199449e+018 2.43e+013 0.00e+000 3.48e+009 
    9 1.8788865e+016 -1.8834049e+016 2.61e+012 0.00e+000 3.73e+008 
    10 1.1565062e+015 -1.1745630e+015 5.17e+011 0.00e+000 7.39e+007 
    11 1.8402445e+014 -1.9572763e+014 5.36e+010 0.00e+000 7.67e+006 
    12 2.3338839e+013 -3.9167399e+013 6.84e-001 0.00e+000 3.16e+003 
    13 -2.0461928e+013 -1.0305044e+013 2.72e-001 0.00e+000 1.81e+003 
    14 -8.5727163e+013 -2.7114059e+012 1.92e-001 0.00e+000 9.54e+002 
    15 -1.2863131e+014 -4.3393850e+011 1.74e-001 0.00e+000 1.69e+003 
    16 -3.3998821e+014 -6.2601017e+010 2.44e-001 0.00e+000 1.63e+002 
    17 -4.8972995e+014 -8.9929658e+009 3.81e-001 0.00e+000 8.95e+001 
    18 -8.0163587e+014 -1.2980223e+009 3.85e-001 0.00e+000 3.06e+001 
    19 -9.9926360e+014 -1.9645121e+008 8.59e-002 0.00e+000 2.50e+001 
    20 -2.3645253e+015 -3.3591755e+007 1.85e-001 0.00e+000 1.81e+001 
    21 -2.3645489e+015 -3.6655103e+007 3.93e-001 0.00e+000 1.82e+001 
    22 -2.3665146e+015 -4.2775757e+007 3.87e-001 0.00e+000 1.80e+001 
    23 -2.4122749e+015 -5.0062938e+007 5.21e-001 0.00e+000 1.76e+001 
    24 -2.5774166e+015 -1.0009577e+007 1.46e+000 0.00e+000 1.88e+001 
    25 -2.5830270e+015 -1.6715236e+007 1.81e+000 0.00e+000 1.87e+001 
    26 -3.2012216e+015 -5.6710775e+006 5.38e-001 0.00e+000 1.75e+001 
    27 -7.5080027e+015 -1.9991081e+006 1.72e+000 0.00e+000 1.74e+001 
    28 -1.4664526e+016 -9.4070118e+005 9.55e-001 0.00e+000 1.74e+001 
    29 -1.4671054e+016 -2.3754747e+006 5.81e+000 0.00e+000 1.74e+001 
    30 -1.4675288e+016 -5.8554481e+006 4.72e+000 0.00e+000 1.75e+001 
    31 -1.4688208e+016 -1.5933011e+007 4.63e+000 0.00e+000 1.75e+001 
    32 -1.4820493e+016 -5.0999417e+007 5.64e+000 0.00e+000 1.76e+001 
    33 -1.8009464e+016 -1.0809049e+007 4.77e+000 0.00e+000 1.74e+001 
    34 -2.1147351e+016 -1.5196820e+007 5.82e+001 0.00e+000 1.74e+001 
    35 -3.1087060e+016 -4.1509264e+006 1.79e+001 0.00e+000 1.74e+001 
    36 -4.6998748e+016 -1.5490984e+006 6.66e+000 0.00e+000 1.74e+001 
    37 -6.6410451e+016 -9.0730197e+005 1.00e+001 0.00e+000 1.73e+001 
    38 -6.6412915e+016 -1.2692245e+006 2.97e+001 0.00e+000 1.74e+001 
    39 -6.6421938e+016 -2.3703454e+006 2.11e+001 0.00e+000 1.74e+001 
    40 -6.6467293e+016 -7.3051760e+006 5.57e+001 0.00e+000 1.74e+001 
    41 -6.6608951e+016 -1.9147451e+007 3.27e+001 0.00e+000 1.75e+001 
    42 -6.7172366e+016 -6.3713529e+007 2.44e+001 0.00e+000 1.75e+001 
    43 -6.8996611e+016 -1.6047844e+008 3.13e+001 0.00e+000 1.74e+001 
    44 -7.5224067e+016 -2.9844653e+008 2.22e+001 0.00e+000 1.74e+001 
    45 -8.8541981e+016 -2.9298621e+008 1.93e+001 0.00e+000 1.72e+001 
    46 -1.5484919e+017 -7.7191292e+009 1.99e+001 0.00e+000 1.68e+001 
    47 -2.4846059e+017 -2.0001282e+009 4.10e+001 0.00e+000 1.67e+001 
    48 -2.9179330e+017 -3.4143835e+009 6.96e+001 0.00e+000 1.81e+001 
    49 -3.0331831e+017 -8.6988051e+009 6.82e+001 0.00e+000 1.79e+001 
    50 -5.0822921e+017 -5.3511719e+009 9.99e+001 0.00e+000 1.61e+001 
    51 -8.7831029e+017 -1.1762106e+009 2.51e+001 0.00e+000 1.62e+001 
    52 -1.2006404e+018 -6.0523067e+009 1.75e+002 0.00e+000 1.87e+001 
    * -2.5774166e+015 -1.0009577e+007 1.46e+000 0.00e+000 1.88e+001 
Barrier time = 5.75 sec. (1675.34 ticks) 

Total time on 4 threads = 5.75 sec. (1675.34 ticks) 
Solution status = 6 : 

Answer 1

是的，这意味着一个解决方案是可行的，但不是最佳

reference 1

我建议你尝试不同的算法，默认情况下，LP设置为自动或原始单纯，也许改变算法可帮助为

reference 2

你解决的LP或MI P +

编辑 然后可能的话，有一个解决方案，但有没有办法实现，因为一些限制/约束不能达到

如果你尝试你可能有运气（如果这是可能的你问题）写一个小脚本，一次创建一个模型约束，解决它，并且如果可能当你添加约束号50时，它会再次返回状态码6，你跳过这个约束并继续约束到51等等

或者，您可以循环约束，临时禁用一个约束并解决问题，然后重新启用事后纳克，并移动到下一个找到这些约束是给你的问题

此外，this可能有一定的帮助