Abstract. The most kinds of generalized
convexities cannot resist perturbations, even linear ones, while real
application problems are often affected by disturbances, both linear and
nonlinear ones. For instance, we showed earlier that quasiconvexity,
explicit quasiconvexity, and pseudoconvexity cannot withstand arbitrarily
small linear disturbances to keep their characteristic properties, and
convex functions are the only ones which can resist every linear
disturbance to preserve property “each local minimizer is a global
minimize”, but it fails if perturbation is nonlinear, even with arbitrarily
small supremum norm. In this paper, we present some sufficient conditions
for the outer γconvexity and the inner γconvexity of disturbed
functions, for instance, when convex functions are added with arbitrarily
wild but accordingly bounded functions. That means, in spite of such
nonlinear disturbances, some weakened properties can be saved, namely the properties
of outer γconvex functions and inner γconvex ones. For
instance, each γminimizer of an outer γconvex function f: D > R
defined by $f(x^*)=\inf_{x\in\bar
B(x^*,\gamma)\cap D}f(x)$ is a global minimizer, or if an inner
γconvex function f: D > R
defined on some bounded convex subset D
of an inner product space attains its supremum, then it does so at least at
some strictly γextreme point of D,
which cannot be represented as midpoint of some segment $[z', z'']\subset
D$ with $\z'z''\\geq 2\,\gamma$, etc.

Keywords: Generalized convexity, rough convexity,
outer γconvex function, inner γconvex function, perturbation of
convex function, selfJung constant, γextreme
point.
