linear_programming: raise on simplex non-convergence

[Kcstring]

Describe your change:

Fixes #14584
Fixes #15047
Fixes #15243

Tableau.run_simplex() now raises a descriptive ValueError when Tableau.maxiter is exhausted instead of silently returning {}. This lets callers distinguish a non-converged or cycling tableau from a real empty solution.

The doctest temporarily sets Tableau.maxiter = 0 to cover the non-convergence path deterministically.

• Add an algorithm?
• Fix a bug or typo in an existing algorithm?
• Add or change doctests? -- Note: Please avoid changing both code and tests in a single pull request.
• Documentation change?

Checklist:

• I have read CONTRIBUTING.md.
• This pull request is all my own work -- I have not plagiarized.
• I know that pull requests will not be merged if they fail the automated tests.
• This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
• All new Python files are placed inside an existing directory.
• All filenames are in all lowercase characters with no spaces or dashes.
• All functions and variable names follow Python naming conventions.
• All function parameters and return values are annotated with Python type hints.
• All functions have doctests that pass the automated testing.
• All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
• If this pull request resolves one or more open issues then the description above includes the issue number(s) with a closing keyword: "Fixes #ISSUE-NUMBER".

Testing:

• python3 -m pytest linear_programming/simplex.py
• python3 -m ruff check linear_programming/simplex.py

[priya-sundaram-dev]

Correct fix for #14584: replaces the silent return {} with an informative ValueError on non-convergence, and the doctest is nicely self-verifying (sets maxiter=0, asserts the raise, restores it) with no new files. My recommended pick for this bug (triage in #15081). Thanks @Kcstring!