Bridging Passenger Perception and Timetable Optimisation: Empirically Derived Satisfaction Weights for Rail Transit Scheduling

Existing timetable optimisation models for urban rail transit predominantly adopt operator-oriented objectives with assumed passenger-related weights. This paper proposes a passenger satisfaction-oriented timetable optimisation framework in which satisfaction weights are empirically derived from confirmatory factor analysis and Cramér’s V analysis of survey data collected from 439 passengers on Nanning Rail Transit Line 1. Seven scheduling-related service attributes are formally expressed as functions of timetable decision variables, establishing a direct linkage between passenger perception and scheduling decisions. A multi-objective model minimises a weighted combination of passenger dissatisfaction, operational cost, and stranded passenger ratio, solved by a Passenger Satisfaction-oriented Adaptive Dispatch Heuristic (PS-ADH) integrating simulated annealing with a passenger flow simulation module. Case study results demonstrate simultaneous improvements of 3.78% in composite objective value, 3.25% in passenger dissatisfaction, and 3.25% in operational cost, with a 27.4% reduction in stranded passengers. The optimised strategy is selected consistently across all ten random initialisations (CV = 0.13%). Sensitivity analysis reveals a structural break at cost weight β=0.4, beyond which the optimal strategy shifts qualitatively toward cost minimisation at the expense of service quality. The framework provides a transferable methodology for integrating passenger perception data into rail transit scheduling for emerging urban rail systems.