On the Use of Multi-Objective Optimization Algorithms for Solving the Impairment Aware-RWA Problem

In future transparent optical networks, it is important to consider the impact of physical impairments in the routing and wavelengths assignment process, to achieve efficient connection provisioning. In this paper, we use classical multi-objective optimization (MOO) strategies and particularly genetic algorithms to jointly solve the impairment aware RWA (IA-RWA) problem. Fiber impairments are indirectly considered through the insertion of the path length and the number of common hops in the optimization process. It is shown that blocking is greatly improved, while the obtained solutions truly converge towards the Pareto front that constitutes the set of global optimum solutions. We have evaluated our findings, using an Q estimator tool, that calculates the signal quality of each path analytically.