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

Table 3

Inferences of geometrical track maintenance methods.

Author Reference	Evaluation Scheme	Concentrated segment	Parameters involved	Tools Employed	Research Gap
[7]	Case study	Track maintenance	Track alignment defects	Decision support systems	Probability prediction of alert limits
[8]	Case study	Track maintenance	Total cost/renewal actions/speed restrictions	Mathematical modelling	Degradation parameters/different network configuration
[9]	Case study	Track maintenance	Track alignment parameters	HBM/Monte Carlo Simulation	Model sensitivity/correlation of formulation
[10]	Case study	Track maintenance	Track alignment parameters	Markov decision process	Permissible speed restriction
[15]	Case study	Track maintenance	Track alignment parameters	Weibull approach	Improvement of TPI
[47]	Case study	Rail maintenance	Rail parameters	VirMaLab/Bayesian models	Integration of meta-heuristics
[51]	Case study	Rail maintenance	Location/time of defect occurrence/defect type	Markov decision process/Whittle indices	Crew assignment for maintenance operations
[57]	Case study	Track maintenance	Rail type length/allowable speed/ballast type/fastener type/passenger capacity	Monte Carlo simulation/K-means clustering algorithm	Reduction of maintenance cost
[58]	Case study	Track maintenance	Maintenance window/frequency of inspection	Monte Carlo simulation/sensitivity analysis	Increase frequency and response time for maintenance
[59]	Case study	Track maintenance	Track geometry inspection values	Heuristics/analytical framework	Time optimization
[60]	Case study	Track quality	Track indices/longitudinal level	Linear regression analysis	Best fit integrated model
[47]	Case study	Track maintenance	Longitudinal level, alignment, gauge, twist, and cross-level.	Dagum distribution	Fitness of the model for varying track components
[48]	Case study	Track maintenance	Track alignment levels/standard deviation	Mathematical modelling/MILP/Monte Carlo process	Maintenance cost