> Discrete Optimization > Solving Mixed Integer Programming Problems (MIP) > Troubleshooting MIP Performance Problems > Subproblem Optimization

In some problems, you can improve performance by evaluating how the continous LP, QP, or QCP subproblems are solved at the nodes in the branch & cut tree, and then possibly modifying the choice of algorithm to solve them. You can control which algorithm ILOG CPLEX applies to the initial relaxation of your problem separately from your control of which algorithm ILOG CPLEX applies to other subproblems. The following sections explain those parameters more fully.

RootAlg Parameter

The RootAlg algorithm parameter indicates the algorithm for ILOG CPLEX to use on the initial subproblem. In a typical MIP, that initial subproblem is usually the linear relaxation of the original MIP. By default, ILOG CPLEX starts the initial subproblem with the dual simplex optimizer. You may have information about your problem that indicates another optimizer could be more efficient. Table 13.14 summarizes the values available for the RootAlg parameter.

To set this parameter:

Table 13.14 Settings of RootAlg and NodeAlg Parameters
Concert Technology Enumeration 
Callable Library Symbolic Constant 
Setting 
Calls this Optimizer 
Auto 
CPX_ALG_AUTO 
automatic 
Primal 
CPX_ALG_PRIMAL 
primal simplex 
Dual 
CPX_ALG_DUAL 
dual simplex (default) 
Network 
CPX_ALG_HYBNETOPT 
network simplex 
Barrier 
CPX_ALG_BARRIER 
barrier with crossover 
Sifting 
CPX_ALG_SIFTING 
sifting 
Concurrent 
CPX_ALG_CONCURRENT 
concurrent: allowed at root, but not at nodes 

NodeAlg Parameter

The NodeAlg parameter indicates the algorithm for ILOG CPLEX to use on node relaxations other than the root node. By default, ILOG CPLEX applies the dual simplex optimizer to subproblems, and unlike the RootAlg parameter it is extremely unusual for this to not be the most desirable choice, but again, you may have information about your problem that tells you another optimizer could be more efficient. The values and symbolic constants are the same for the NodeAlg parameter as for the RootAlg parameter in Table 13.14.

To set the NodeAlg parameter:

Note
Only simplex and barrier optimizers can solve problems of type QP (quadratic term in the objective function).Only the barrier optimizer can solve problems of type QCP (quadratic terms among the constraints).