Forum Discussion
How to reduce memory usage by the solver?
We have a large model and it ran out of memory when it is starting concurrent solve with dual and barrier method. So is it possible to just pick one method here to reduce the memory requirement? Than...
It seems there is a little confusion about how the LPFLAGS bit control works: This control allows for a custom mix of root LP algorithms.
You activate dual simplex by setting bit 0 (value 1) to 1, you activate barrier by setting bit 2 (value 4) to 1. Therefore, setting LPFLAGS = 4 activates barrier, but disables dual simplex. LPFLAGS = 1 activates only dual simplex. Mixing both (the current behavior) is achieved by setting LPFLAGS = 5.
In python, you therefore use
p = xpress.problem()
p.setControl('lpflags', 1) # or 4to only run your favorite LP algorithm.
It is common that one algorithm solves a root LP faster than the other, so it is a good practice to choose that algorithm only.
