A multi-objective approach for routing and wavelength converter allocation under uncertainty

Wavelength Division Multiplexing (WDM) networks are designed for long-term operations in which the uncertainty of future traffic plays an important role. The performance of these networks is highly dependent on the routing and the wavelength-converter allocation algorithms. In order to achieve a good performance on a long-term basis, both problems have to be dealt with together and traffic uncertainty should be included. To this aim, this work proposes a joint optimization approach where the converters allocation plan and paths for routing are calculated simultaneously. A Multi-Objective Evolutionary Algorithm (MOEA) is proposed to minimize the number of wavelength converters, the average blocking probability, and an unfairness measure, all three at the same time, the uncertainty is modelled by means of a set of scenarios. The proposed MOEA calculates an approximation to the optimal set of solutions. This work presents experimental results showing the feasibility of the proposed approach in a multi-objective and uncertain context.