Capacity and flow assignment of data networks by generalized Benders decomposition

A mixed-integer non-linear model is proposed to optimize jointly the assign ment of capacities and flows (the CFA problem) in a communication network. Discrete capacities are considered and the cost function combines the insta llation cost with a measure of the Quality of Service (QoS) of the resultin g network for a given traffic. Generalized Benders decomposition induces co nvex subproblems which are multicommodity flow problems on different topolo gies with fixed capacities. These are solved by an efficient proximal decom position method. Numerical tests on small to medium-size networks show the ability of the decomposition approach to obtain global optimal solutions of the CFA problem.