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In this paper, the performance of the variables: makespan time, defective fraction due to operator fatigue and direct labor cost, in a job shop manufacturing system is presented. Two methods are compared; the first one blends elements from VEGA and MOGA algorithms (V&M), while the second one corresponds to a weighted sums method (WSM). Applying these methodologies, it was found that the method V&M has a better performance than the WSM. Comparing he variable makespan time (in hours) the first is better by 7.0 %; comparing the variable makespan time (in weeks) by 6.7 %; and comparing the variable defective fraction by 1.4 %. Regarding the variable labor costs, both methods have the same performance. [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]