Parametric Optimization and Related Topics IIJürgen Guddat |
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ALGORITHM ALGORITHM JUMP ALGORITHM PATH analysis applied argminF assume assumptions Attouch Banach space Berlin compute condition connected component consider constraints continuous convergence convex function convex polynomials convex programming defined denote descent differentiable efficiency Ekeland's variational principle example exists f and g feasible set finite function g.c. point GOTO Guddat Hence holds inequalities iteration Jongen Kummer Lagrange multiplier Lemma LICQ linear linearly independent Lipschitz lower semicontinuous mapping Math Mathematical Programming matrix MFCQ minimizer N(wo neighborhood nonlinear programs obtain optimal value optimization problems paper Parametric Optimization pathfollowing perturbations point of Type polynomial Proof properties Proposition prove real number relaxation method Remark robot satisfied semi-infinite solving space stability results stationary point stationary solution strongly stable subdifferential sufficient Suppose t₁ Tammer turning point vector Y₂