A heuristic for the continuous capacity and flow assignment

This work deals with the Continuous Capacity and Flow Assignment (CFA) problem for the design of computer networks. This is a nonconvex optimization problem which has been usually solved by applying local optimization techniques. By rephrasing the problem in the context of concave programming and bringing an alternative formulation of the projected pairwise multicommodity flow polyhedron, a heuristic method for the search of a global minimum of the CFA is proposed. Its implementation is discussed, and computational tests with real backbone networks show that the proposed method compares favorably to previous approaches.