Optimal wavelength converter allocation: a new approach based MOEA

With the incorporation of the wavelength division multiplexing technology in optical networks, wavelength converters allocation has become a key strategy to minimize blocking probability. The optimal wavelength converter allocation (OWCA) problem has been treated partially as a single-objective problem minimizing the number of wavelength converters subject to blocking probability constrains or alternatively, minimizing the blocking probability subject to cost constrains. Both objective functions are in conflict. Therefore, this work proposes a multi-objective optimization approach, based on a multi-objective evolutionary algorithm (MOEA), where the blocking probability and the number of wavelength converters are simultaneously minimizing. Extensive simulations prove that the proposed approach obtains better experimental results than a state of the art alternative.

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