Variational Sufficiency and Solution Stability in Optimization

Abstract

Variational stability, in the sense of local good behavior of optimal values and solutions in problems of optimization under shifts in parameters, is important not only for validating model robustness in practical applications but also for confidence of outcomes in the design of solution algorithms. Fundamental results are presented here about how such stability relates to a recently developed sufficient condition for local optimality called strong variational sufficiency.