CPLEX 无解检测

CPLEX provides tools to help you analyze the source of the infeasibility in your model. Those tools include the conflict refiner and FeasOpt:

（CPLEX 可以分析模型的无解，包括两个工具：conflict refiner and FeasOpt）

• The conflict refiner is invoked by the routine CPXrefineconflict in the Callable Library or by the method refineConflict in Concert Technology. It finds a set of conflicting constraints and bounds in a model and refines the set to be minimal in a sense that you declare. It then reports its findings for you to take action to repair that conflict in your infeasible model. For more about this feature, see Diagnosing infeasibility by refining conflicts.

• FeasOpt is implemented in the Callable Library by the routine CPXfeasopt and in Concert Technology by the method feasOpt. For more about this feature, see Repairing infeasibility: FeasOpt.

With the help of those tools, you may be able to modify your problem to avoid infeasibility.

The algorithms for detecting and refining conflicts do their work by including or removing a constraint or bound in trial solutions, not by varying the data of those entities.

（对于无解的检测是在做尝试解时  通过括入和去除约束或者边界）

Distinguishes a conflict from an irreducibly inconsistent set (IIS).

（(IIS)的全名）

The declaration of infeasibility comes from presolve. In fact, presolve has already performed various reductions by the time it detects the unresolvable infeasibility in constraint c8.

（不可行的检测结果来自预处理，各种简化用于检测不可行解）

a minimal conflict can be refined from an infeasible model regardless of how the infeasibility was found. The infeasibility may have been proven by presolve, by the continuous optimizers, or by the mixed integer optimizer

（最小冲突能够被找到但是无视怎样找到这个不可行解，这个不可行解有可能通过预计算，连续优化，混合整数规划的计算得到）

IloCplex::feasOpt works in two phases. In its first phase, it attempts to minimize its relaxation of the infeasible model. That is, it attempts to find a feasible solution that requires minimal change. In its second phase, it finds an optimal solution among those that require only as much relaxation as it found necessary in the first phase.

(分两步，第一找到可行解，通过最小的改变；第二步，找打一个最优解从第一步相同改变数量的问题)