Power transformers have a key role in the power system grids. Their manufacturing and design must consider several aspects, such as technical limits, legal constrains, security constrains and manufacturing price. Considering only power transformers’ active parts, it is possible to identify 20 manufacturing specific parameters, and in economic point of view, 13 variables are also considered. Using a classic approach, variables are chosen accordingly with the defined constraints, followed by a sensitivity analysis preformed to each variable, to optimize the manufacturing cost. This procedure can be time consuming and the optimum may not be reached. In this paper, genetic algorithms are used. An innovative approach through the introduction of genetic compensation concept in mutation operator is detailed. Results pointed out an increased performance and consistency when compared with the classical approach.