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Mathematical Programming with Data Perturbations

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Table of Contents

Discretization and mesh-independent of Newton's method for generalized differentiability of optimal solutions in non-linear parametric optimization; characterisations of Lipschitzian stability in nonlinear programming; on second order sufficient conditions for structured nonlinear programs in infinite-dimensional function spaces; algorithmic stability analysis for certain trust region methods; a note on using linear knowledge to solve efficiency linear programs specified with approximate data; on the role of the Mangasarian-Fromovitz constraint qualification for penalty-, exact penalty-, and Lagrange multiplier methods; Hoffman's error bound for systems of convex functions and applications to nonlinear optimization; on well-posedness and stability analysis optimization; convergence of approximations to nonlinear optimal control problems; a perturbation-based duality classification for max-flow min-cut problems of Strang and Iri; central and peripheral results in the study of marginal and performance functions; topological stability of feasible sets in semi-infinite optimization - a tutorial; solution existence for infinite quadratic programming; sensitivity analysis of nonlinear programming problems via minimax functions; parametric linear complementary problems; sufficient conditions for weak sharp minima of order two and directional derivatives of the value function.

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