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Convexity and concavity properties of the optimal value function in parametric nonlinear programming. (English) Zbl 0556.90085

Convexity and concavity properties of the optimal value function \(f^*\) are considered for the general parametric optimization problem P(\(\epsilon)\) of the form \(\min_{x} f(x,\epsilon)\), s.t. \(x\in {\mathbb{R}}(\epsilon)\). Such properties of \(f^*\) and the solution set map \(S^*\) form an important part of the theoretical basis for sensitivity, stability, and parametric analysis in mathematical optimization. Sufficient conditions are given for several standard types of convexity and concavity of \(f^*\), in terms of respective convexity and concavity assumptions on f and the feasible region point-to-set map R. Specializations of these results to the general parametric inequality- equality constrained nonlinear programming problem and its right-hand- side version are provided.

MSC:

90C31 Sensitivity, stability, parametric optimization
90-02 Research exposition (monographs, survey articles) pertaining to operations research and mathematical programming
49M37 Numerical methods based on nonlinear programming
Full Text: DOI

References:

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