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This paper presents an analysis of applying the optimization of mean-variance mapping technique in the problem of estimating the parameters of the soil model of two horizontal layers. This problem consists of determining the parameters of the soil model from experimental measurements of apparent resistivity obtained with Wenner method, minimizing the mean square error between values of the experimental and theoretical resistivity curves, which are calculated with mathematical expressions and soil parameters acquired through the optimization of mean-variance mapping technique. Several tests were carried out with resistivity measurements that correspond to different soil types, the results were contrasted with those reported in the technical literature and metaheuristics implemented. In conclusion, according to the results, the performance of the optimization of mean-variance mapping technique was found to be superior than other analyzed optimization techniques. [ABSTRACT FROM AUTHOR]

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]