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In this paper, we develop a fuzzy analytical model, which solves a multiobjective problem in multicast transmission with static trees over GMPLS networks. A model proponed by Donoso [4] was used. The multiobjective problem is solved through metaheuristic wit h evolutionary algorithms, in this case SPEA2 solving a NP-Hard problem in polynomial time. Additionally, a Fuzzy Evolutionary Algorithm based on SPEA2 is implemented. Finally, the comparison between FSPEA2 and SPEA2 is realized and we are giving some conclusions. [ABSTRACT FROM AUTHOR]

This paper presents a multi-objective optimization method which is an alternative solution for multicast networks load balancing, using a software implementation of the Simulated Annealing heuristic. The method minimize four basic parameters necessaries for guarantee the quality of service (QoS) in multicast transmissions, these are: end-to-end delay, maximum link utilization, bandwidth consumption and hop count. The results obtained by the heuristic will be compared with the results hurtled by the mathematical pattern proposed in previous investigations. [ABSTRACT FROM AUTHOR]

In this paper, an analysis of evolutionary algorithms for multi objective optimization, Non-dominated Sorting Genetic Algorithm (NSGA-II) and Strength Pareto Evolutionary Algorithm (SPEA-II) is presented. For this analysis, is taken as reference an optimization problem in a multicast data network, which has as objective functions the hop count and transmission delay. The algorithms performance is compared in tree different networks. Moreover, the model for two of this topologies using GAMS tool is resolved and results are compared with the NSGA-II and SPEA-II algorithms proposed. Problem results show the algorithms performance in their solution. [ABSTRACT FROM AUTHOR]