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In this paper we propose efficient operators for a well known multi-objective evolutionary optimizer, called NSGA II, applied to design all-optical networks regarding the network topology and the device specifications in order to both minimize the capital expenditure to build the network and to maximize the overall network performance. From the experiments, we perceived that it is better to use an uniform crossover, to include preferences a priori and to initialize the individuals emphasizing the network topology.

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We propose a methodology which applies a multi-objective Evolutionary Algorithm, the NSGAII, in order to design transparent optical networks, aiming to minimize simultaneously the total cost to build the network, the blocking probability and the energy consumption during operation. The optimizer provides a set of nondominated solutions and, after that, the designer can decide which solution is more suitable for a specific case. We believe these three different important aspects must be taken into account during the design process. However, just some few papers tackle energy consumption from a physical network design perspective. Besides, to the best of our knowledge, none of the previous presented proposals consider all these issues simultaneously.