Branch-and-bound decomposition approach for solving quasiconvex-concave programs

A class of branch-and-bound methods is proposed for minimizing a quasiconvex-concave function subject to convex and quasiconvex-concave inequality constraints. Several important special cases where the subproblems involved by the bounding-and-branching operations can be solved quite effectively include certain d.c. programming problems, indefinite quadratic programming with one negative eigenvalue, affine multiplicative problems, and fractional multiplicative optimization.This research was accomplished while the second author was a Fellow of the Alexander von Humboldt Foundation at the University of Trier, Trier, Germany.