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This paper presents a multiobjective analysis including variables of the environment of the energy system which is conditioned by the use of solid fuels, for this reason the analysis includes the external characteristics of the resource (fuel) of residue (ash) and the product (electricity/steam). The energy system used is Termocesar, a Colombian process for generating electricity from carbon. Three functions named thermoeconomic objective function, technology objective function and environmental objective function, are analyzed to establish the best location of the energy The genetic algorithm method is used for the optimization of the system. The results were analyzed for nine combinations of weights and show that for most of the cases the optimum includes coals from the Department of Cesar in Colombia. [ABSTRACT FROM AUTHOR]

To improve the quality of service in cell systems, techniques of Dynamic Assignment Channels are used to reduce the probability of blocking calls. In this paper an algorithm of assignment channels is required to reduce the probability of blocking, extending the system capacity to add new calls. This is obtained by using an interchange of channels of current calls and reducing the restrictions of electromagnetic compatibility. According to this, the algorithm has to provide solutions of commitments between two different objectives; on the one hand reduce the amount of assignments, and on the other to do the same with the level of interference due to the flexible restrictions of electromagnetic compatibility. A heuristic focus based on the evolution paradigm is presented to solve the multi-objective optimization problem. Two evolutionary multi-objective algorithms (SPEAII y NSGA II) are compared by the use of two different metrics. The results show that the proposed methodology can be applied to different generations of mobile communication systems. [ABSTRACT FROM AUTHOR]

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]

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]