A review of passenger-oriented railway rescheduling approaches

European Transport Research Review

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Table 4 Summary for approaches for rescheduling in urban rail transit

Paper	Capacity	Type	Rescheduling measures	Rescheduling models	Passenger details	Objective function minimized	Solution approach
Almodovar and Garcia-Rodenas [35]	TC + TSC	D	RT + C + RSR	O	D	GTT	H (Greedy heuristics)
Zhen and Jing [36]	TC + SC	P	RT	O	D	GTT + TEC	M (Genetic algorithm)
Xu et al. [37]	TC + SC + TSC	P	RT	IP	S	GTT	M (Genetic algorithm)
Yin et al. [38]	TC + SC + TSC	P	RT + SC	O	D	TPD + TEC	H (Approximate dynamic programming)
Hao et al. [39]	TC + SC + TSC	P	RT + SC	O	D	TDP + SC + NSP	H (Approximate dynamic programming)
Li et al. [34]	TC + SC + TSC	P	RT	O	D	PEC	M (Model predictive control)
Hou et al. [40]	TC + SC + TSC	P	RT + ST	MIP	D	TTD + TEC + NSP	E (Commercial solvers)
Gao et al. [41]	TC + SC + TSC	P	RT + SS	MIP	D	TDP + NSP	H (Heuristic iterative algorithm)
Altazin et al. [42]	TC + SC + RSC	P	RT + SS	IP	S	WTS	E (Commercial solver)
Hassannayebi et al. [44]	TC + SC + TSC	P	RT + SS + ST	O	D	WTS	M (Variable neighbourhood search)
Cadarso et al. [43]	TC + SC + TSC + RSC	D	C + E	MIP	D	PEC	H (Two step iterative heuristics)