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The choice of the right maintenance strategy is an important but also difficult topic for every energy utility. The difficulty consists in the huge number of interacting cost parameters. The present paper shows how from the biology well known process is adapted as an optimization algorithm in order to handle the parameter diversity. Outgoing from the definition of Life Cycle Cost and a method for substation reliability calculation the main idea of genetic algorithm and its application for Life Cycle Cost optimization is presented. Closing a case study shows the suitability of the algorithm.