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bundles / scipy 1.17.1 / scipy / optimize / _linprog_simplex

module

scipy.optimize._linprog_simplex

source: /scipy/optimize/_linprog_simplex.py :0

Members

Summary

Simplex method for linear programming

Extended Summary

The simplex method uses a traditional, full-tableau implementation of Dantzig's simplex algorithm [1], [2] (not the Nelder-Mead simplex). This algorithm is included for backwards compatibility and educational purposes.

Warnings

The simplex method may encounter numerical difficulties when pivot values are close to the specified tolerance. If encountered try remove any redundant constraints, change the pivot strategy to Bland's rule or increase the tolerance value.

Alternatively, more robust methods maybe be used. See 'interior-point' <optimize.linprog-interior-point> and 'revised simplex' <optimize.linprog-revised_simplex>.

Additional content

Simplex method for linear programming

The simplex method uses a traditional, full-tableau implementation of Dantzig's simplex algorithm [1], [2] (not the Nelder-Mead simplex). This algorithm is included for backwards compatibility and educational purposes.

Warnings

The simplex method may encounter numerical difficulties when pivot values are close to the specified tolerance. If encountered try remove any redundant constraints, change the pivot strategy to Bland's rule or increase the tolerance value.

Alternatively, more robust methods maybe be used. See 'interior-point' <optimize.linprog-interior-point> and 'revised simplex' <optimize.linprog-revised_simplex>.

References

[1]

Dantzig, George B., Linear programming and extensions. Rand Corporation Research Study Princeton Univ. Press, Princeton, NJ, 1963

[2]

Hillier, S.H. and Lieberman, G.J. (1995), "Introduction to Mathematical Programming", McGraw-Hill, Chapter 4.

Aliases

  • scipy.optimize._linprog_simplex