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Linear Programming
Solves a Linear Programming problem (maximization only) by Dantzig's
simplex method. |
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| m, mle |
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Constraints: 'm', total;
and 'mle', "≤"-type.
(No ' ≥ ' constraints.) |
| n |
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Structural variables · |
| c |
Intermediate output (t, f) and coefficients in the
objective function ·
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| A |
Constraint matrix
(RHS constraint [<ret> RHS constraint] …)
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Solves a Linear Programming problem in "standard" form, only for
maximization.
The coefficients, c, in the objective function must be
preceded by t or f (true, false) for intermediate output.
(To minimize, multiply the coefficients by −1.)
The constraint matrix, A, must be given beginning
(in each row) with the right-hand side (RHS) constant (with 'return' at
end of line). So, e.g.,
− x1 + 4 x2 ≤ 78 would
become 78 −1 4.
This Problem tries to imitate the manual resolution by the
matrix method. For a more secure resolution:
NAG
based version.
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References:
• Wagner, Harvey M., 1972+,
"Principles of Operations
Research, with applications to managerial decisions",
John Wiley, New York, NY (USA). |
