Review Article

[Retracted] Maintenance Methodologies Embraced for Railroad Systems: A Review

Table 2

Inferences of statistical track maintenance methods.

Author ReferenceEvaluation SchemeConcentrated segmentParameters involvedTools employedResearch gap

[5]Case studyTrack maintenanceFrequency of tamping operationMixed integer programming model (MILP)Cost structure/schedule generation

[6]Case studyTrack maintenanceRail grinding schedule/rail crack detectionInteger programming model (ILP)/polyhedral analysisMaintenance decision-making process/frequency of inspections

[24]Case studyTrack geometryInspection/intervention/renewalPetri net formulationTrack length/tamping machine

[25]Real timeTrack maintenanceSegments/routine works/possession costTMS strategy/Sensitivity analysisCalibration of the PMSP model

[29]Case studyTrack maintenance scheduleMaintenance activities/risk assessmentModular model architecture/ILPOnline recovery tool to determine stochastic delays

[32]Case studyTrack degradationRail load, rail type, rail profileAdaptive network-based fuzzy inference system (ANFIS) modelGauge value prediction

[33]Case studyTrack maintenanceTime period/track component replacementInteger programming model (ILP)/Heuristic algorithmsUnexpected interventions/corrective maintenance decisions

[36]Case studyTrack maintenanceUser cost/environmental costRAMS/LCCADatabase management

[37]Case studyTrack maintenanceBallast type/lab test/trafficLife cycle approachLife cycle cost analysis (LCCA) and life cycle assessment (LCA)

[38]Case studyTrack maintenanceRail, ballast, sleepers, and switchesBinary integer programming (IP) modelLimitation of possession time

[39]Real timeTrack maintenance clusteringProject duration/job cluster typeMixed integer mathematical programming model (MIMP)Randomness of algorithm

[40]Case studyTrack interactive rolling setsWheel diameter/mileageMarkov decision process/MDP toolbox-MATLABMarkov transition matrix (MTM)/inspection modes/precision

[41]Case studyTrack maintenanceRail grinding/renewalMarkov decision processRail curvature