The Generalized Multiobjective Multitree model (GMM-model) considers, for the first time, multitree-multicast load balancing with splitting in a multiobjective context. The mathematical solution of the GMM-model is a whole Pareto optimal set that includes several previously published results, according to surveyed publications. To solve the GMM-model, this paper proposes a multi-objective evolutionary algorithm (MOEA) inspired by the Strength Pareto Evolutionary Algorithm (SPEA). Experimental results considering up to 11 different objectives are presented for the well-known NSF network, with two simultaneous data flows.
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