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Titlebook: Generalized Convexity; Proceedings of the I Sándor Komlósi,Tamás Rapcsák,Siegfried Schaible Conference proceedings 1994 Springer-Verlag Ber

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Waqar Hussain,Jari Nurmi,Fabio Garzianctions are also discussed. Under appropiate assumptions of univexity, optimality conditions and duality results for Mond-Weir duality are established. In the end some suggestions for further research have been made.
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Trajectory Analysis for Drivingelop the study via a recently proposed approach [3]: the image space analysis. This approach has showed many interesting developments in many topics of optimization theory (optimality conditions, penalty methods, duality theory etc). We show that, also in this field, it represents a powerful tool for developing the analysis.
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Univex sets, functions and univex nonlinear programmingnctions are also discussed. Under appropiate assumptions of univexity, optimality conditions and duality results for Mond-Weir duality are established. In the end some suggestions for further research have been made.
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Equivalence between generalized gradients and subdifferentials for a suitable class of lower semiconncide. This class includes, for instance, the convex functions, the .. perturbations of convex functions, the primal lower-nice functions (see [16]). As application we find a convergence theorem for the generalized gradients of a Γ-convergent sequence of functions which have a .-monotone subdifferential of order one (with . independent on .).
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Generalizing convexity for second order optimality conditionstakes into account the structure of the feasible set and thus enables us to narrow the usual gap between necessary and sufficient optimality conditions. In section 2 we deal with quadratic problems for which we specify similar global optimality conditions.
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Abstract nonsmooth nonconvex programminghn-Tucker type for abstract cone-constrained programming problems. In addition these techniques are applied to quasidifferentiable programming problems and similar necessary conditions and sufficient optimality conditions using generalized convexity are established.
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