Multiobjective Optimization for Railway Maintenance Plans

Daniel Peralta, Christoph Bergmeir, Martin Krone, Marta Galende, Manuel Menéndez, Gregorio I. Sainz-Palmero, Carlos Martinez Bertrand, Frank Klawonn, Jose M. Benitez

    Research output: Contribution to journalArticleResearchpeer-review

    10 Citations (Scopus)

    Abstract

    Railway track maintenance is a critical problem for any railway administrator. More precisely, preventive maintenance scheduling is a nondeterministic polynomial time (NP)-hard problem, which additionally involves multiple objectives such as economic cost, maximum capacity, serviceability, safety, and passenger comfort. This paper proposes a multiobjective optimization approach to this problem, combined with a track deterioration model that takes into account the degradation caused by maintenance operations. The track behavior is simulated by an exponential deterioration model based on a two-level segmentation. The maintenance schedule is built using a Pareto-based algorithm with two objectives (cost and delay) and three constraints, on top of an initialization heuristic based on expert knowledge. The proposed approach has been tested with two different algorithms (NSGA-II and AMOSA) over a model of a real track to create schedules for different horizons ranging between 3 and 20 years. The solutions obtained by AMOSA outperform those designed by human experts both in terms of time delay and economic cost, demonstrating the capability of the proposal to produce near-optimal long-term maintenance schedules.

    Original languageEnglish
    Article number04018014
    Pages (from-to)1-11
    Number of pages11
    JournalJournal of Computing in Civil Engineering
    Volume32
    Issue number3
    DOIs
    Publication statusPublished - 1 May 2018

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