Convex composite multi-objective nonsmooth programming
Mathematical Programming: Series A and B
Perturbation Analysis of a Condition Number for Linear Systems
SIAM Journal on Matrix Analysis and Applications
Optimality conditions in mathematical programming and composite optimization
Mathematical Programming: Series A and B
Error bounds in mathematical programming
Mathematical Programming: Series A and B - Special issue: papers from ismp97, the 16th international symposium on mathematical programming, Lausanne EPFL
Nonsmooth analysis and control theory
Nonsmooth analysis and control theory
Hoffman's Error Bound, Local Controllability, and Sensitivity Analysis
SIAM Journal on Control and Optimization
On the Sensitivity Analysis of Hoffman Constants for Systems of Linear Inequalities
SIAM Journal on Optimization
On the Calmness of a Class of Multifunctions
SIAM Journal on Optimization
Subdifferential Conditions for Calmness of Convex Constraints
SIAM Journal on Optimization
Error Bounds for Lower Semicontinuous Functions in Normed Spaces
SIAM Journal on Optimization
Perturbation Analysis of Error Bounds for Systems of Conic Linear Inequalities in Banach Spaces
SIAM Journal on Optimization
Metric Subregularity and Constraint Qualifications for Convex Generalized Equations in Banach Spaces
SIAM Journal on Optimization
Error bounds for systems of lower semicontinuous functions in Asplund spaces
Mathematical Programming: Series A and B - Nonlinear convex optimization and variational inequalities
Subdifferential characterization of approximate convexity: the lower semicontinuous case
Mathematical Programming: Series A and B - Nonlinear convex optimization and variational inequalities
Linear Regularity for a Collection of Subsmooth Sets in Banach Spaces
SIAM Journal on Optimization
Stability of Error Bounds for Semi-infinite Convex Constraint Systems
SIAM Journal on Optimization
Metric Subregularity and Calmness for Nonconvex Generalized Equations in Banach Spaces
SIAM Journal on Optimization
Stability of Error Bounds for Convex Constraint Systems in Banach Spaces
SIAM Journal on Optimization
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The stability of error bounds is significant in optimization theory and applications. Based on either the linearity assumption or the convexity and finite dimension assumption, several authors have focused on perturbation analysis of error bounds and obtained valuable results. Mainly motivated by Ngai, Kruger, and Théra [SIAM J. Optim., 20 (2010), pp. 2080-2096], in a general Banach space, we study the stability of error bounds for inequalities determined by proper lower semicontinuous quasi-subsmooth functions which are a very large class of nonconvex functions (in particular, approximate convex functions, primal-lower-nice functions, and convexly composite functions satisfying the Robinson qualification). We also consider the stability of error bounds for infinite constraint systems determined by infinitely many uniformly quasi-subsmooth functions. In particular, we extend the main results of Ngai, Kruger, and Théra to the infinite dimensional and nonconvex setting.