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This paper compares and analyzes the economics of alternative maintenance plans for generating stations. The usual life-cycle investment decisions for power plant equipment involve definition of alternative scenarios with specified refurbishment dates. The aim of the paper is to present a method for the selection of optimal investment dates that minimizes the life-cycle cost of the analyzed equipment. The system is introduced as a distributed web-based software application. The methodology based on combining evolutionary programming with Monte Carlo simulations is described and illustrated by a numerical example involving analysis of the optimal timing of new investments for refurbishment of a large generator at a thermal-generating plant.