Multiobjective Multitree model solution using MOEA

Abstract

In a previous paper a novel Generalized Multiobjective Multitree model (GMM-model) was proposed. This model considers for the first time multitree-multicast load balancing with splitting in a multiobjective context, whose mathematical solution is a whole Pareto optimal set that can include several results than it has been possible to find in the publications surveyed. To solve the GMM-model, in this paper a multi-objective evolutionary algorithm (MOEA) inspired by the Strength Pareto Evolutionary Algorithm (SPEA) is proposed. Experimental results considering up to 11 different objectives are presented for the well-known NSF network, with two simultaneous data flows. Key-Word: Multicast, Splitting, Traffic Engineering, Load Balancing, Multiobjective.

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Cite this paper

@inproceedings{Barn2005MultiobjectiveMM, title={Multiobjective Multitree model solution using MOEA}, author={Benjam{\'i}n Bar{\'a}n and Jos{\'e} Lu{\'i}s Marzo}, year={2005} }