Stability in E

We define and analyze two kinds of stability in E-convex programming problem in which the feasible domain is affected by an operator E. The first kind of this stability is that the set of all operators E that make an optimal set stable while the other kind is that the set of all operators E that make certain side of the feasible domain still active

Characterizations of Asymptotic Cone of the Solution Set of a Composite Convex Optimization Problem

We characterize the asymptotic cone of the solution set of a convex composite optimization problem. We then apply the obtained results to study the necessary and sufficient conditions for the nonemptiness and compactness of the solution set of the problem. Our results generalize and improve some known results in literature

Higher order duality in multiobjective fractional programming with support functions

AbstractIn this paper a new class of higher order (F,ρ,σ)-type I functions for a multiobjective programming problem is introduced, which subsumes several known studied classes. Higher order Mond–Weir and Schaible type dual programs are formulated for a nondifferentiable multiobjective fractional programming problem where the objective functions and the constraints contain support functions of compact convex sets in Rn. Weak and strong duality results are studied in both the cases assuming the involved functions to be higher order (F,ρ,σ)-type I. A number of previously studied problems appear as special cases

Second-order optimality conditions for problems with C1 data

AbstractIn this paper we obtain second-order optimality conditions of Karush–Kuhn–Tucker type and Fritz John one for a problem with inequality constraints and a set constraint in nonsmooth settings using second-order directional derivatives. In the necessary conditions we suppose that the objective function and the active constraints are continuously differentiable, but their gradients are not necessarily locally Lipschitz. In the sufficient conditions for a global minimum x¯ we assume that the objective function is differentiable at x¯ and second-order pseudoconvex at x¯, a notion introduced by the authors [I. Ginchev, V.I. Ivanov, Higher-order pseudoconvex functions, in: I.V. Konnov, D.T. Luc, A.M. Rubinov (Eds.), Generalized Convexity and Related Topics, in: Lecture Notes in Econom. and Math. Systems, vol. 583, Springer, 2007, pp. 247–264], the constraints are both differentiable and quasiconvex at x¯. In the sufficient conditions for an isolated local minimum of order two we suppose that the problem belongs to the class C1,1. We show that they do not hold for C1 problems, which are not C1,1 ones. At last a new notion parabolic local minimum is defined and it is applied to extend the sufficient conditions for an isolated local minimum from problems with C1,1 data to problems with C1 one

Nonlinear Lagrangian for multiobjective optimization and applications to duality and exact penalization

Author name used in this publication: Yang, X. Q.2002-2003 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

A nonlinear Lagrangian approach to constrained optimization problems

Author name used in this publication: Yang, X. Q.2000-2001 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe