Fix simplex max iteration failure and optimize pivot operation

[MeriemBchini]

Summary

This PR improves both correctness and performance of the simplex algorithm implementation.

Previously, run_simplex() silently returned an empty dictionary when the maximum iteration limit was reached, making failures hard to detect and debug.

This update introduces explicit error handling and optimizes the pivot operation for better performance.

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Changes

• Replaced silent failure (return {}) with a descriptive ValueError when maximum iterations are exceeded
• Added iteration tracking for clearer debugging information
• Optimized pivot operation using NumPy vectorization (removes Python loop)
• Improved type safety and removed unsafe typing patterns
• Fixed minor code quality and style issues to align with repository standards

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Why this matters

This change improves:

• Correctness: failures are now explicit instead of silent
• Debuggability: users get clear error messages when convergence fails
• Performance: pivot step is now vectorized, reducing runtime overhead on large tableaus
• Maintainability: cleaner and more readable implementation

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Behavior Change

Before:

run_simplex() → {}

After:

Raises:

[algorithms-keeper]

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