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Optimize LinExpr multiplication by one or zero
See original GitHub issueI’m working on a problem that is mathematically defined with a couple of big sparse binary matrices, I’m using quite a lot of python-mip binary variables and I collected them into numpy tensors to have some syntactic sugar and matrix operations over them.
It’s very nice but very very slow, and it seems to me that with some basic optimization it could perform much better, notably to the LinExpr.__mul__() function.
Would it be reasonable to have the special cases for multiplication by 1 or 0 to speed up this kind of use?
Issue Analytics
- State:
- Created 3 years ago
- Comments:14 (14 by maintainers)
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a faster LinExpr is the priority but my idea is also to make a available a low level interface to communicate with the solver. With CFFI it is possible to allocate C arrays, which can be directly passed to CBC, for example, this would be a “last resort” for those who want to the maximum performance.
release 1.9.0 resolve this issue for me, I’d close it