[KEY FEATURE] Debug problem formulation
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 25
- Forks
- 5
- PR merge metrics
- No merged PRs in 30d
Description
When the solver does not return "optimal" but something else that is an issue, like "infeasible" - the analyst should be able to explore what happened and why - such as seeing if there are conflicting constraints.
Consider leveraging this package or similar:
MathOptInterface.jl
has functions like:
- compute_conflict!
- copy_conflict
- primal_feasibility_report
- relax_with_penalty!
Package is in Julia but pretty sure it can run from a standard solver output file (MPS).
Contributor guide
No contributing guide indexed for this repository
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by reviewing how standard solver output files, including MPS, are handled and how non-optimal statuses are exposed to analysts. Compare the proposed MathOptInterface.jl functions—compute_conflict!, copy_conflict, primal_feasibility_report, and relax_with_penalty!—with the project’s needs. Done means analysts can investigate infeasible or otherwise non-optimal results and identify conflicting constraints.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- julia, python
- Domain
- backend
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Quiet
- Clarity
- Needs clarification
- Newbie friendliness
- 35/100