Abstract

In this paper, we deal with a preventive maintenance (PM) scheduling and spare parts problems for a rolling stock system. We determine the optimal PM interval and the optimal number of spare parts for components in the rolling stock system to minimize the system life cycle cost during satisfying the system target availability. The system availability and system life cycle cost are estimated by simulation. A genetic algorithm and a simulated annealing are proposed to find the optimal PM intervals and the optimal spare parts number of all components. Numerical examples are also studied.

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