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This paper presents a mixed integer linear programming model for optimizing maintenance and renewal costs for urban rail networks over mid- and long-term horizons. By focusing on planning maintenance and renewal activities, the proposed model optimizes expensive renewal and maintenance costs over the lifetime of the rail curve while considering industrial constraints related to the degradation of rail tracks and rail possessions. The proposed optimization model is compared to a baseline rule-based strategy, demonstrating significant cost reductions, with savings of up to 6.93% in some cases and a decrease in the number of performed maintenance activities. The optimization approach adjusts renewal dates to balance curve lifespan extension and cost minimization, leading to earlier renewal dates. This reduction in activities also contributes to sustainability by reducing environmental impacts. The long-term implications of the model are discussed. In many cases, considerable cumulative cost savings and indirect environmental benefits are achieved by the proposed approach.
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Saiem et al. (2025) studied this question.
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