This paper is devoted to the problems of
minimizing and maximizing a quasiconvex
function over an arbitrary set.
First, we formulate global optimality
conditions and then, based on them, propose
algorithms for the case in which the objective
function is convex and the feasible set is
nonconvex and compact.
The proposed algoritms are shown to be
globally convergent. Some computational
results are presented.