Genetic algorithm for solving survivable network design with simultaneous unicast and anycast flows

Abstract

We consider the survivable network design problem for simultaneous unicast and anycast flow requests. In this problem, a network is modeled by a connected, weighted and undirected graph with link cost follows All Capacities Modular Cost (ACMC) model. Given a set of flow demand, this problem aims at finding a set of connection with minimized network cost to protect the network against any single failure. This problem is proved to be NP-hard. In this paper, we propose a new Genetic Algorithm for solving the ACMC Survivable Network Design Problem (A-SNDP). Extensive simulation results on Polska, Germany and Atlanta network instances show that the proposed algorithm is much more efficient than the Tabu Search and other baseline algorithms such as FBB1 and FBB2 in terms of minimizing the network cost. © Springer-Verlag Berlin Heidelberg 2013.