Abstract
In this work, we tackle a real-world telecommunication problem by using Evolutionary Computation and Multiobjective Optimization jointly. This problem is known in the literature as the Traffic Grooming problem and consists on multiplexing or grooming a set of low-speed traffic requests (Mbps) onto high-speed channels (Gbps) over an optical network with wavelength division multiplexing facility. We propose a multiobjective version of an algorithm based on the laws of motions and mass interactions (Gravitational Search Algorithm, GSA) for solving this NP-hard optimization problem. After carrying out several comparisons with other approaches published in the literature for this optical problem, we can conclude that the multiobjective GSA (MO-GSA) is able to obtain very promising results.
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Rubio-Largo, Á., Vega-Rodríguez, M.A. (2013). A Multiobjective Approach Based on the Law of Gravity and Mass Interactions for Optimizing Networks. In: Middendorf, M., Blum, C. (eds) Evolutionary Computation in Combinatorial Optimization. EvoCOP 2013. Lecture Notes in Computer Science, vol 7832. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37198-1_2
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DOI: https://doi.org/10.1007/978-3-642-37198-1_2
Publisher Name: Springer, Berlin, Heidelberg
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