HiGHS for column generation #1466
Replies: 7 comments 4 replies
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That makes about four projects that I know of using HiGHS for column generation! What you described is correct and will be efficient. If you add columns using 'Highs::addColumns' then HiGHS will automatically update its internal basis - the new columns will be nonbasic - and won't even have to refactor the basis matrix when you next call 'Highs::run'. You're talking as if you'll be solving the master with simplex. There is a strong argument to use interior point, since that yields a possibly valuable stabilisation of the dual values. The downside is that interior point doesn't hot start. |
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@jajhall yeah, we focus on primal simplex, but we could experiment with IP as well. Is 'Highs::addColumns' part of the model or the solver? I cannot really find a complete documentation of the various interfaces... |
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There isn't great documentation for HiGHS. In terms of concepts, start from What language are you using? The "incumbent" model and solvers are tightly integrated, and I can see that causes confusion. So, when you call a model modification method like |
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We use C++. So from the cpp example I see that
So you will call addColum on the solver, not on the model? |
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Following this topic, recently I've managed to build a column generation and branch-and-price algorithm using Highs's python interface and I would love to add it as an example. Would you be interested? |
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I am looking at a CG for a huge LP, so maybe I am in a simpler spot...a good example is more than welcome! |
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Hello, I've added an issue and submitted a new pull request with the branch-and-price example. As a somewhat minimal example I think it's fine, but I'm sure that there is space for improvement, specially at the branching part. In any case, please take a look and let me know if any changes are required. |
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Hi,
I am considering HiGHS for to implement a column generation approach, but it is unclear to me how I should proceed.
For what I can see the way is to
the last point is what troubles me the most:
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