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linear_programming: raise on simplex non-convergence #14600

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linear_programming: raise on simplex non-convergence #14600

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15 changes: 14 additions & 1 deletion linear_programming/simplex.py
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Original file line number Diff line number Diff line change
Expand Up @@ -285,6 +285,15 @@ def run_simplex(self) -> dict[Any, Any]:
... [1, 0, 0, 0, 0, 0, -1, 0, 1, 2.0]
... ]), 2, 2).run_simplex().items()} # doctest: +ELLIPSIS
{'P': 132.0, 'x1': 12.000... 'x2': 5.999...}

>>> original_maxiter = Tableau.maxiter
>>> Tableau.maxiter = 0
>>> Tableau(np.array([[-1, -1, 0, 0, 0], [1, 3, 1, 0, 4],
... [3, 1, 0, 1, 4.0]]), 2, 0).run_simplex()
Traceback (most recent call last):
...
ValueError: No convergence within 0 iterations; may be cycling/unbounded.
>>> Tableau.maxiter = original_maxiter
"""
# Stop simplex algorithm from cycling.
for _ in range(Tableau.maxiter):
Expand All @@ -302,7 +311,11 @@ def run_simplex(self) -> dict[Any, Any]:
self.tableau = self.change_stage()
else:
self.tableau = self.pivot(row_idx, col_idx)
return {}
msg = (
f"No convergence within {Tableau.maxiter} iterations; "
"may be cycling/unbounded."
)
raise ValueError(msg)

def interpret_tableau(self) -> dict[str, float]:
"""Given the final tableau, add the corresponding values of the basic
Expand Down