Algorithmic Approximation of Optimal Value Differential Stability Bounds in Nonlinear Programming,
RAND CORP SANTA MONICA CA
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The data needed to calculate the sensitivity to data perturbations of the solution and optimal value of a mathematical program are available as by-products of many solution. Fiacco demonstrated this is developing a penalty function technque for approximating the parameter derivatives of a solution for quite general perturbed non-linear programs. Armacost and Mylander used this to advantage in making available the routine calculation of sensitivity information as part of a computer code for the Sequential Unconstrained Minimization Technique SUMT.
- Theoretical Mathematics