With the development of financial risk management, the notion of convex risk measures has been proposed and has gained more and more attentions. Utility-based shortfall risk (SR), as a specific and important class of convex risk measures, has become popular in recent years. In this paper we...

We give an equation reformulation of the Karush–Kuhn–Tucker (KKT) condition for the second order cone optimization problem. The equation is strongly semismooth and its Clarke subdifferential at the KKT point is proved to be nonsingular under the constraint nondegeneracy condition and a...

Matrix conic optimization induced by spectral norm (MOSN) has found important applications in many fields. This paper focus on the optimality conditions and perturbation analysis of the MOSN problem. The Karush–Kuhn–Tucker (KKT) conditions of the MOSN problem can be reformulated as a...

We give an equation reformulation of the Karush–Kuhn–Tucker (KKT) condition for the second order cone optimization problem. The equation is strongly semismooth and its Clarke subdifferential at the KKT point is proved to be nonsingular under the constraint nondegeneracy condition and a...

Matrix conic optimization induced by spectral norm (MOSN) has found important applications in many fields. This paper focus on the optimality conditions and perturbation analysis of the MOSN problem. The Karush–Kuhn–Tucker (KKT) conditions of the MOSN problem can be reformulated as a...

We consider an inverse quadratic programming (QP) problem in which the parameters in both the objective function and the constraint set of a given QP problem need to be adjusted as little as possible so that a known feasible solution becomes the optimal one. We formulate this problem as a linear...

In this paper, we consider a class of mathematical programs governed by second-order cone constrained parameterized generalized equations. We reformulate the necessary optimality conditions as a system of nonsmooth equations under linear independence constraint qualification and the strict...

The focus of this paper is on studying an inverse second-order cone quadratic programming problem, in which the parameters in the objective function need to be adjusted as little as possible so that a known feasible solution becomes the optimal one. We formulate this problem as a minimization...