Method
Algorithm used to solve continuous models
| Type: | int |
|---|---|
| Default value: | -1 |
| Minimum value: | -1 |
| Maximum value: | 5 |
Algorithm used to solve continuous models or the root node of a MIP model. Options are: -1=automatic, 0=primal simplex, 1=dual simplex, 2=barrier, 3=concurrent, 4=deterministic concurrent, 5=deterministic concurrent simplex.
In the current release, the default Automatic (-1) setting will typically choose non-deterministic concurrent (Method=3) for an LP, barrier (Method=2) for a QP or QCP, and dual (Method=1) for the MIP root node. Only the simplex and barrier algorithms are available for continuous QP models. Only primal and dual simplex are available for solving the root of an MIQP model. Only barrier is available for continuous QCP models.
Concurrent optimizers run multiple solvers on multiple threads simultaneously, and choose the one that finishes first. Deterministic concurrent (Method=4) and deterministic concurrent simplex (Method=5) gives the exact same result each time, while Method=3 is often faster but can produce different optimal bases when run multiple times. Deterministic concurrent simplex (Method=5) will run both primal and dual simplex, while deterministic concurrent will run barrier, primal simplex and dual simplex at the same time.
The default setting is rarely significantly slower than the best possible setting, so you generally won't see a big gain from changing this parameter. There are classes of models where one particular algorithm is consistently fastest, though, so you may want to experiment with different options when confronted with a particularly difficult model.
Note that if memory is tight on an LP model, you should consider using the dual simplex method (Method=1). The concurrent optimizer, which is typically chosen when using the default setting, consumes a lot more memory than dual simplex alone.
For examples of how to query or modify parameter values from our different APIs, refer to our Parameter Examples.
