We show that many problems of global optimization can be converted into convex-concave programs which can be solved by a decomposition procedure combining branch-and-bound techniques with cutting plane methods. The algorithms use adaptive rectangular and simplicial subdivisions which are not necessarily exhaustive but sufficient to guarantee convergence.