A scheduling strategy considering demand variation during the day and within the network is outlined. The optimal headway is calculated taking into account demand and supply simultaneously achieving equilibrium. The train service structure is complicated due to different headways for each hour of the day and various parts of the network. Short train headways shall be provided for sections with high demand whereas sections with lower demand (outskirts) request easily recallable departure times.

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... hat is why the use of Genetic Algorithms is proposed to transform such an operating scheme into an optimal train service. They allow to find a timetable with non-conflicting train paths, which is characterized by even headways for all sections of the network. The timetable can also be optimized for minimal fleet size or both goals simultaneously. In order to ease the application of such operating strategies, the proposed algorithms were implemented into a computer-aided planning system called ALFa which is described in this paper.