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Computability and complexity of polynomial optimization problems
Identification by model reference adaptive systems
Matching problems with Knapsack side constraints A computational study
7 other sections not shown
algorithm Anal analysis applications approximation assume assumptions AVERAGE AVERAGE AVERAGE Berlin bounded Broyden's method compact computation cone consider convergence convex function convex set Corollary critical point decomposition defined denote differential equations differential inclusions discretization dual duality error Euler method example exists feasible set finite formula global growth condition H.Th Hence holds inequality infinite dimensional Initial Value Problem int(C integer iterations Jongen Kuhn-Tucker points Kummer Lagrangean Lemma LICQ linear linear subspace Lipschitz continuity Lipschitzian LSIP matching problem Math Mathematical method MFCQ minimal elements minimal solution Morse Morse theory neighborhood Newton's method non-empty Nonl nonlinear programming nonsmooth norm optimal control optimal control problem optimality conditions parametric perturbations polynomial Proof properties quantifier elimination quasiconvex real numbers relaxation Runge-Kutta methods satisfied semi-infinite programming sequence solve space Springer-Verlag stability subset Theorem theory topological variables weakly minimal