I have implemented a linear programme using Linopy and use the HiGHS solver to solve it with the interior point method.
For this application, I don't need to run crossover on the solution. When I pass the run_crossover='off' option to HiGHS through linopy, HiGHS behaves as expected and skips the crossover step, however, linopy does not consider the model optimised when this step is omitted. Do you know how to obtain the solution from linopy in this scenario?
Example log message from HiGHS:
Ipx: IPM optimal
WARNING: LP solver residuals: primal = 0.0710581; dual = 0.0473415 yield num/max/sum primal (391784/0.0710581/6.24267) and dual (463677/0.0473415/3.47325) corrections
WARNING: Unwelcome IPX status of Unknown: basis is not valid; solution is valid; run_crossover is "off"
Model name : linopy-problem-m_vf1rkb
Model status : Unknown
IPM iterations: 48
Objective value : -2.8809874134e+07
Relative P-D gap : 7.5484672674e-01
HiGHS run time : 141.71
Writing the solution to /private/var/folders/4p/qywpknvj5qx89qh1g6vy1qlc0000gn/T/linopy-solve-28b76k6g.sol
And the following log message from linopy:
Solution status unknown. Trying to parse solution.
Optimization failed:
Status: unknown
Termination condition: unknown
Solution: 1786176 primals, 1456848 duals
Objective: -2.88e+07
Solver model: available
Solver message: unknown
This issue can be resolved by upgrading to the latest version of linopy. The example error runs off v0.3.15. Once upgraded to v0.5.0, this is no longer a problem.