CPLEX - 访问解决方案 C++ 时出错

CPLEX - Error in accessing solution C++

我在访问 LP 问题的解决方案时遇到问题。

这是调用 cplex.solve() 后 CPLEX 的输出;

 CPXPARAM_MIP_Strategy_CallbackReducedLP          0
 Found incumbent of value 0.000000 after 0.00 sec. (0.70 ticks)
 Tried aggregator 1 time.
 MIP Presolve eliminated 570 rows and 3 columns.
 MIP Presolve modified 88 coefficients.
 Reduced MIP has 390 rows, 29291 columns, and 76482 nonzeros.
 Reduced MIP has 29291 binaries, 0 generals, 0 SOSs, and 0 indicators.
 Presolve time = 0.06 sec. (49.60 ticks)
 Tried aggregator 1 time.
 Reduced MIP has 390 rows, 29291 columns, and 76482 nonzeros.
 Reduced MIP has 29291 binaries, 0 generals, 0 SOSs, and 0 indicators.
 Presolve time = 0.04 sec. (31.47 ticks)
 Probing time = 0.02 sec. (1.36 ticks)
 MIP emphasis: balance optimality and feasibility.
 MIP search method: dynamic search.
 Parallel mode: deterministic, using up to 8 threads.
 Root relaxation solution time = 0.03 sec. (17.59 ticks)

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

*     0+    0                            0.0000     -395.1814              --- 
*     0+    0                         -291.2283     -395.1814            35.69%
*     0     0      integral     0     -372.2283     -372.2283      201    0.00%
 Elapsed time = 0.21 sec. (131.64 ticks, tree = 0.00 MB, solutions = 3)

 Root node processing (before b&c):
   Real time             =    0.21 sec. (133.18 ticks)
 Parallel b&c, 8 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) =    0.21 sec. (133.18 ticks)

但是当我调用 cplex.getValues(values, variables);程序给出一个 SIGABRT 信号并抛出以下异常:

libc++abi.dylib: terminating with uncaught exception of type IloAlgorithm::NotExtractedException

这是我的代码。我做错了什么?

std::vector<links_t> links(pointsA.size()*pointsB.size());

std::unordered_map<int, std::vector<std::size_t> > point2DToLinks;

for(std::size_t i=0; i<pointsA.size(); ++i){

  for(std::size_t j=0; j<pointsB.size(); ++j){

    std::size_t index = (i*pointsA.size()) + j;

    links[index].from = i;
    links[index].to   = j;

    links[index].value = cv::norm(pointsA[i] - pointsB[j]);

    point2DToLinks[pointsA[i].point2D[0]->id].push_back(index);
    point2DToLinks[pointsA[i].point2D[1]->id].push_back(index);
    point2DToLinks[pointsA[i].point2D[2]->id].push_back(index);

    point2DToLinks[pointsB[j].point2D[0]->id].push_back(index);
    point2DToLinks[pointsB[j].point2D[1]->id].push_back(index);
    point2DToLinks[pointsB[j].point2D[2]->id].push_back(index);

  }

}

std::size_t size = links.size() + point2DToLinks.size();

IloEnv environment;

IloNumArray coefficients(environment, size);

for(std::size_t i=0; i<links.size(); ++i)    coefficients[i] = links[i].value;
for(std::size_t i=links.size(); i<size; ++i) coefficients[i] = -lambda;

IloNumVarArray variables(environment, size, 0, 1, IloNumVar::Bool);

IloObjective objective(environment, 0.0, IloObjective::Minimize);

objective.setLinearCoefs(variables, coefficients);

IloRangeArray constrains = IloRangeArray(environment);

std::size_t counter = 0;

for(auto point=point2DToLinks.begin(); point!=point2DToLinks.end(); point++){

  IloExpr expression(environment);

  const std::vector<std::size_t> & inLinks = point->second;

  for(std::size_t j=0; j<inLinks.size(); j++) expression += variables[inLinks[j]];

  expression -= variables[links.size() + counter];

  constrains.add(IloRange(environment, 0, expression));

  expression.end();

  ++counter;

}

IloModel model(environment);

model.add(objective);
model.add(constrains);

IloCplex cplex(model);

cplex.solve();

if(cplex.getStatus() != IloAlgorithm::Optimal){
  fprintf(stderr, "error: cplex terminate with an error.\n");
  abort();
}

IloNumArray values(environment, size);

cplex.getValues(values, variables);

for(std::size_t i=0; i<links.size(); ++i)
  if(values[i] > 0) pairs.push_back(links[i]);

environment.end();

如果您向 CPLEX 询问 CPLEX 的模型中没有的变量值,则会发生此错误。当您构建模型时,仅声明和定义要包含在模型中的变量是不够的。它还必须是约束之一或模型中 objective 的一部分。因此,您 declare/define 未包含在其中一个约束或 objective 中的任何变量将不在提取到 CPLEX 内部工作中的变量集中。您可以采取两种显而易见的措施来解决此问题。

首先,您可以尝试在变量循环内获取变量值,并测试每个值是否确实在 cplex 模型中 - 我认为它类似于 cplex.isExtracted(var)。做一些简单的事情,例如当您遇到未提取的变量时打印一条消息,告诉您哪个变量导致了问题。

其次,您可以将模型从 CPLEX 导出为 LP 格式文件并手动检查。这是一种非常有用的方法,可以查看模型中的实际内容,而不是您认为模型中的内容。