CPLEX: Optimal solution with unscaled infeasibilities is thrown out
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- Python
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Description
Hi everyone, I have an issue with CPLEX. for some problems, which Highs can solve, I get an unknown status from linopy, with the message that the problem is optimal with unscaled infeasibilities. As I understand, CPLEX introduced the solution of the scaled problem to the unscaled problem, and there were some slight infeasibilities, which usually do not mean a lot (see for examle here: http://iea-etsap.org/forum/showthread.php?tid=162)
Linopy, however, seems to not import this solution, potentially because the status is unknown and not optimal. Would it be possible to change this, so that linopy simply imports this solution, even though there might be slight infeasibilities?
Best,
Georg
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Research direction
The issue names linopy's CPLEX solution-status handling but provides no file, test, or reproducible model. Trace how linopy interprets CPLEX's "optimal with unscaled infeasibilities" status, then compare it with the status of an equivalent problem Highs can solve. Done means the available CPLEX solution is imported instead of being reported as unknown.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- backend
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 38/100