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Generalized Multiobjective Multitree model solution using MOEA

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

World Scientific and Engineering Academy and Society

Author: Barán, Benjamín
Fabregat Gesa, Ramon
Donoso Meisel, Yezid
Solano Donado, Fernando
Marzo i Lázaro, Josep Lluís
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
Document access: http://hdl.handle.net/2072/218103
Language: eng
Publisher: World Scientific and Engineering Academy and Society
Rights: Tots els drets reservats
Subject: Telecomunicació -- Tràfic
Telecommunication -- Traffic
Ordinadors, Xarxes d’
Computer networks
Title: Generalized Multiobjective Multitree model solution using MOEA
Type: info:eu-repo/semantics/article
Repository: Recercat

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