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Design method for s-CO2 gas turbine power plants

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Design method for s-CO2 gas turbine power plants ( design-method-s-co2-gas-turbine-power-plants )

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4-3 Optimization of the net present value of a solar tower power plant 89 into the next generation. The fitness function is defined according to the Pareto optimality criteria and returns the fitness value which is used to select the best solutions from a given population. The solutions with a low qualification are discarded and the new generation goes through the modification process, which includes the crossover and mutation. Crossover is the process of combining two different designs, generating new solutions between them. The next operation is the mutation, which is a random process that alters some parts of a genetic string. Since there may not be a definitive answer to the issued problem it may not be obvious when to stop. Then it is recommendable to produce as many populations as possible according to the available computational resources and time. In this regard, a specific time limit or number of generations can be imposed as the criteria to continue or stop the loop. The Pareto optimality concept is not embedded into the fundamentals of the genetic algorithms, which is why an optimal solution can be generated and then die in the process. In order to avoid this the optimal solutions should be stored independently as they arise [81]. Master of Science Thesis J.S. Bahamonde Noriega

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