In this article, we address a real life optimization problem, the rail track inspection scheduling problem. This problem consists of scheduling railway network inspection tasks. The objective is to minimize the total deadhead distance while performing all inspection tasks. Different 0-1 integer formulations for the problem are presented. A heuristic based on both Benders and Dantzig-Wolfe decompositions is proposed to solve this rich arc routing problem. Its performance is analyzed on a real life dataset provided by the French national railway company. The proposed algorithm is compared to a dynamic programming-based heuristic. Its ability to schedule the inspection tasks of 1 year on a sparse graph with thousand nodes and arcs is assessed.

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