Recently developed methods of monotonic optimization have been applied successfully for studying a wide class of nonconvex optimization problems, that includes, among others, generalized polynomial programming, generalized mul-tiplicative and fractional programming, discrete programming, optimization over the efficient set, complementarity problems, etc. In… (More)
We propose an algorithm to locate a global maximum of an increasing function subject to an increasing constraint on the cone of vectors with nonnegative coordinates. The algorithm is based on the outer approximation of the feasible set. We establish the convergence of the algorithm and provide a number of numerical experiments. We also discuss the types of… (More)
An analysis is given of the errors that have occured in some recent publications on d.c. optimization.
A rigorous foundation is presented for the decomposition method in nonconvex global optimization, including parametric optimization, partly convex, partly monotonic, and mono-tonic/linear optimization. Incidentally, some errors in the recent literature on this subject are pointed out and fixed.