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Nowadays heuristic methods are one of the most used tools for the optimization of problems. The proof of that is the fact that they are widely used in chemistry, economics and energy. Among the most popular of heuristic methods belong the genetic algorithms. They can handle difficult, large-scale problems with many parameters, like the optimization of the hydrothermal coordination of hydro and thermal power plants. As with any other method, genetic algorithms also have certain parameters. These parameters, among others, are the size of the population, the maximum number of generations, and the probability of crossovers and mutations. The effect of these parameters on the results of an optimization using genetic algorithms is the focus of this paper. The hydro-thermal coordination of one hydro and one thermal power plant was used as an example to explain this issue.

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Nowadays heuristic methods are one of the most used tools for the optimization of problems. The proof of that is the fact that they are widely used in chemistry, economics and energy. Among the most popular of heuristic methods belongs differential evolution, belonging to the so-called 'evolutionary algorithms'. They can handle difficult, large-scale problems with many parameters, like the optimization of the hydro-thermal coordination of hydro and thermal power plants. As with any other method, differential evolution also has certain parameters. These parameters, among others, are the size of the population, the maximum number of generations, crossover parameter and mutation factor. The effect of these parameters on the results of an optimization using differential evolution is the focus of this paper. The hydro-thermal coordination of one hydro and one thermal power plant was used as an example to explain this issue.

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